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Masters Degrees (Computer Science Research)

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Take advantage of one of our 100 Master’s Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

As an MSc by Research Computer Science student you will be guided by internationally leading researchers in the field of computer science and will carry out a large individual research project. Computer Science is at the cutting edge of modern technology, and is developing rapidly and Swansea Computer Science graduates enjoy excellent employment prospects.

Computer Science now plays a part in almost every aspect of our lives - science, engineering, the media, entertainment, travel, commerce and industry, public services and the home.

The MSc by Research Computer Science degree enables you to pursue a one year individual programme of research in the field of computer science and would normally terminate after a year. However, under appropriate circumstances, this first year of research can also be used in a progression to Year 2 of a PhD degree.

The MSc by Research programmes including Computer Science MSc by Research all have a recommended initial research training module (Science Skills & Research Methods), but otherwise has no taught element and is most suitable for you if you have an existing background in biosciences or cognate discipline and are looking to pursue a wholly research-based programme of study.

As a student of the MSc by Research Computer Science programme you will be fully integrated into one of our established research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Research

The results of the Research Excellence Framework (REF) 2014 show that we lead Wales in the field of Computer Science and are in the UK Top 20.

We are ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

Links with Industry

Each spring, Computer Science students prepare and present a poster about their project at a project fair – usually together with a system or software demonstration. We also strongly encourage students to create CVs and business cards to take along to the fair, as businesses and employers visit to view the range of projects and make contact with the graduating students.

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Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Read more
Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Data scientists help organisations make sense of their data. As data is collected and analysed in all areas of society, demand for professional data scientists is high and will grow higher. The emerging Internet of Things, for instance, will produce a whole new range of problems and opportunities in data analysis.

In the Data Science master’s programme, you will gain a solid understanding of the methods used in data science. You will learn not only to apply data science: you will acquire insight into how and why methods work so you will be able to construct solutions to new challenges in data science. In the Data Science master’s programme, you will also be able to work on problems specific to a scientific discipline and to combine domain knowledge with the latest data analysis methods and tools. The teachers of the programme are themselves active data science researchers, and the programme is heavily based on first-hand research experience.

Upon graduating from the Data Science MSc programme, you will have solid knowledge of the central concepts, theories, and research methods of data science as well as applied skills. In particular, you will be able to:
-Understand the general computational and probabilistic principles underlying modern machine learning and data mining algorithms.
-Apply various computational and statistical methods to analyse scientific and business data.
-Assess the suitability of each method for the purpose of data collection and use.
-Implement state-of-the-art machine learning solutions efficiently using high-performance computing platforms.
-Undertake creative work, making systematic use of investigation or experimentation, to discover new knowledge.
-Report results in a clear and understandable manner.
-Analyse scientific and industrial data to devise new applications and support decision making.

The MSc programme is offered jointly by the Department of Computer Science, the Department of Mathematics and Statistics, and the Department of Physics, with support from the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP), all located on the Kumpula Science campus. In your applied data science studies you can also include multidisciplinary studies from other master's programmes, such as digital humanities, and natural and medical sciences.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The Data Science MSc programme combines elements from computer science and mathematical sciences to provide you with skills in topics such as machine learning, distributed systems and statistical methods. You might also find that knowledge in a particular scientific field is useful for your future career. You can obtain this through minor studies in the MSc programme, or it might already be part of your bachelor-level degree.

Studies in the Data Science MSc programme include both theoretical and practical components, including a variety of study methods (lectures, exercises, projects, seminars; done both individually and in groups). Especially in applied data science, we also use problem-based learning methods, so that you can address real-world issues. You will also practise academic skills such as scientific writing and oral presentation throughout your studies. You are encouraged to include an internship in your degree in order to obtain practical experience in the field.

Minor studies give you a wider perspective of Data Science. Your minor subject can be an application area of Data Science (such as physics or the humanities), a discipline that supports application of Data Science (such as language technology), or a methodological subject needed for the development of new Data Science methods and models (such as computer science, statistics, or mathematics).

Selection of the Major

You can specialise either in the core areas of data science -- algorithms, infrastructure and statistics -- or in its applications. This means that you can focus on the development of new models and methods in data science, supported by the data science research carried out at the University of Helsinki; or you can become a data science specialist in an application field by incorporating studies in another subject. In addition to mainstream data science topics, the programme offers two largely unique opportunities for specialisation: the data science computing environment and infrastructure, and data science in natural sciences, especially physics.

Programme Structure

You should be able to complete the MSc Programme in Data Science of 120 credits (ECTS) in two years of full-time study. The programme consists of:
-Common core studies of basic data science courses.
-Several modules on specific topics within data science algorithms, data science infrastructures and statistical data science, and on data science tools.
-Seminars and colloquia.
-Courses on academic skills and tools.
-Possibly an internship in a research group or company.
-Studies in an application domain.
-Master’s thesis (30 credits).

Career Prospects

Industry and science are flooded with data and are struggling to make sense of it. There is urgent demand for individuals trained to analyse data, including massive and heterogeneous data. For this reason, the opportunities are expected to grow dramatically. The interdisciplinary Data Science MSc programme will train you to work in data-intensive areas of industry and science, with the skills and knowledge needed to construct solutions to complex data analysis problems.

If you are focusing on the core areas of data science, you will typically find employment as a researcher or consultant, sometimes after taking a PhD in Computer Science or Statistics to deepen your knowledge of the field and research methods. If your focus is on the use of data science for specific applications, you will typically find work in industry or in other fields of science such as physics, digital humanities, biology or medicine.

Internationalization

The Data Science MSc is an international programme, with students from around the world and an international research environment. All of the departments taking part in the programme are internationally recognised for their research and a significant fraction of the teaching and research staff come from abroad.

The departments participate in international student exchange programmes and offer you the chance to include international experience as part of your degree. Data Science itself is an international field, so once you graduate you can apply for jobs in any country.

In the programme, all courses are in English. Although the Helsinki area is quite cosmopolitan and English is widely spoken, you can also take courses to learn Finnish at the University of Helsinki Language Centre. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning other languages.

Research Focus

The MSc programme in Data Science is offered jointly by three departments and two research institutes. Their research covers a wide spectrum of the many aspects of data science. At a very general level, the focal areas are:
-Machine learning and data mining
-Distributed computation and computational infrastructures
-Statistical modelling and analysis
-Studies in the programme are tightly connected to research carried out in the participating departments and institutes.

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

The MSc in Computer Science course is for you if you are a graduate from one of a wide range of disciplines and are looking to change direction or because of the needs of your chosen career, require a solid foundation in Computer Science.

As the use of computers and computer based systems continues to grow in all aspects of life, at home and at work, it is apparent that there will be for years to come a need for many people who can combine a knowledge of Computer Science, the discipline that underlies Information Technology, and degree level knowledge in a wide variety of other disciplines.

Over the duration of the MSc Computer Science course you will study a variety of modules taught by academic staff that are part of internationally renowned research groups. The course is also regularly updated to ensure that it keeps pace with the rapid developments in Computer Science.

Key Features of Computer Science MSc

• We are top in the UK for career prospects*
• We are 3rd in the UK for teaching quality**
• 5th in the UK overall*
• 7th in the UK for student satisfaction with 98% [National Student Survey 2016]
• 7th in the UK overall and Top in Wales*
• High employability prospects - we are 8th in the UK for graduate prospects*
• 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
• UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
• Our Project Fair allows students to present their work to local industry
• Strong links with industry
• £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)

*Guardian University Guide 2017
**Times & Sunday Times University Guide 2016

Modules of Computer Science MSc

Modules for the MSc in Computer Science include Computer Science Project Research Methods but please visit our course page for more information.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

94% of our Postgraduate Taught Graduates of Computer Science were in professional level work or study [DLHE 14/15].

Student Profile

“I chose the MSc Computer Science as a conversion from my previous War and Society degree, primarily employment opportunities. The course was by no means easy for me coming from an arts background, and the first few weeks I felt a little over my head, but thanks to the truly stimulating content from the syllabus and the high quality of the teaching within the department I soon caught up and began to thrive on the course. My project revolved around a comparative study of the Haskell Web-Framework Yesod and ASP.NET. During the completion of this I picked up many of the skills that I now use on an everyday basis in my role at Kinspeed (A Sheffield based Software House). Since starting work I have been able to apply many of the skills I obtained during my time at Swansea and have no doubt that choosing to study the MSc Computer Science at Swansea was one of the better decisions of my life.”

Chris Swires

Research

The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

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Leiden University offers five different specialisations in the MSc programme in Computer Science. - Bioinformatics. - Computer Science and Advanced Data Analytics. Read more
Leiden University offers five different specialisations in the MSc programme in Computer Science:

- Bioinformatics
- Computer Science and Advanced Data Analytics
- Computer Science and Science Communication and Society
- Computer Science and Science-Based Business
- Data Science: Computer Science

Visit the website: http://en.mastersinleiden.nl/programmes/computer-science/en/introduction

Course detail

Leiden University offers five different specialisations in the MSc programme in Computer Science.

Three specialisations are dedicated to the research areas of the Leiden Institute of Advanced Computer Science:

- Computer Science and Advanced Data Analytics
- Bioinformatics
- Data Science for Computer Science

The other two specialisations are more broadly oriented, and combine at least one year of the computer science curriculum with training in which specific career opportunities in science-related professions can be explored:

- Computer Science and Science-Based Business.
- Computer Science and Science Communication and Society

Reasons to Choose Computer Science in Leiden:

- The programme offers stimulating, significant and innovative research in the field of Computer Science, including recent advances in Data Analytics and Natural Computing.

- Research at the Leiden Institute of Advanced Computer Science (LIACS) has an excellent international reputation.

- The strength of the programmes is the individual approach: an individually tailored programme will be designed for each student.

- The researchers and assistants are easily accessible. Students and staff work closely together in a research-oriented environment.

- Students with an MSc in Computer Science are admissible to a PhD programme.

- It provides students with a thorough computer science background that will allow them to pursue careers in research or industrial environments.

Careers

Masters of Science in Computer Science are not only professionally trained, they also have an analytical mind and problem-solving attitude. These qualities ensure a wide variety of career opportunities.

Master of Science students in Leiden work in a multinational environment and are being prepared to operate in international settings.

How to apply: http://en.mastersinleiden.nl/arrange/admission

Funding

For information regarding funding, please visit the website: http://prospectivestudents.leiden.edu/scholarships

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Take advantage of one of our 100 Master’s Scholarships to study Computer Science. Informatique at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Computer Science: Informatique at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

The MSc in Computer Science: Informatique is a Dual Degree scheme between Swansea University and Université Grenoble Alpes for computer science.

The MSc in Computer Science: Informatique Grenoble dual degree scheme is a two year programme that provides students with an opportunity to study in both Swansea, UK and Grenoble, France. One year of the Computer Science: Informatique programme students study at Swansea University and the second year of the programme students study at Université Grenoble Alpes. Upon successful completion of the programme, students will receive an M.Sc. in Advanced Computer Science from Swansea University and a Master from Université Grenoble Alpes.

Key Features of Computer Science: Informatique MSc

- We are top in the UK for career prospects [Guardian University Guide 2018]
- 5th in the UK overall [Guardian University Guide 2018]7th in the UK for student satisfaction with 98% [National Student Survey 2016]
- We are in the UK Top 10 for teaching quality [Times & Sunday Times University Guide 2017]
- 12th in the UK overall and Top in Wales [Times & Sunday Times University Guide 2017]
- 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
- UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
- Our Project Fair allows students to present their work to local industry
- Strong links with industry
- £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)
- Top University in Wales [Times & Sunday Times University Guide 2017]

Modules of Computer Science: Informatique MSc

Modules on the MSc in Computer Science: Informatique may include:

Critical Systems; IT-Security: Theory and Practice; Visual Analytics; Data Science Research Methods and Seminars; Big Data and Data Mining; Data Visualization; Human Computer Interaction; Big Data and Machine Learning; Web Application Development; High Performance Computing in C/C++; Software Testing; Graphics Processor Programming; Embedded System Design; Mathematical Skills for Data Scientists; Logic in Computer Science; Computer Vision and Pattern Recognition; High-Performance Computing in C/C++; Hardware and Devices; Modelling and Verification Techniques; Operating Systems and Architectures.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of our expansion, we are building the Computational Foundry on our Bay Campus for computer and mathematical sciences. This development is exciting news for Swansea Mathematics who are part of the vibrant and growing community of world-class research leaders drawn from computer and mathematical sciences.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

94% of our Postgraduate Taught Computer Science Graduates were in professional level work or study [DLHE 14/15].

Some example job titles include:

Software Engineer: Motorola Solutions
Change Coordinator: Logica
Software Developer/Engineer: NS Technology
Workflow Developer: Irwin Mitchell
IT Developer: Crimsan Consultants
Consultant: Crimsan Consultants
Programmer: Evil Twin Artworks
Web Developer & Web Support: VSI Thinking
Software Developer: Wireless Innovations
Associate Business Application Analyst: CDC Software
Software Developer: OpenBet Technologies
Technical Support Consultant: Alterian
Programming: Rock It
Software Developer: BMJ Group

Research

The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

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Research in Computer Science at York is carried out at the frontiers of knowledge in the discipline. This course gives you the chance to study a range of advanced topics in Computer Science, taught by researchers active in that area. Read more
Research in Computer Science at York is carried out at the frontiers of knowledge in the discipline. This course gives you the chance to study a range of advanced topics in Computer Science, taught by researchers active in that area. This means you will be learning current research results, keeping you at the forefront of these areas. You will also learn a range of theories, principles and practical methods.

The MSc in Advanced Computer Science is a full time, one year taught course, intended for students who already have a good first degree in Computer Science, and would like to develop a level of understanding and technical skill at the leading edge of Computer Science.

You can choose modules on a range of topics, including Cryptography, Functional Programming, Interactive Technologies, Natural Language Processing, Quantum Computation and Model-Driven Engineering.

Course aims
You will gain an in-depth knowledge of topics on the frontiers of Computer Science in order to engage in research or development and application of leading-edge research findings.

By undertaking an individual project, you will become a specialist in your selected area. You will be encouraged to produce research results of your own. This will prepare you to undertake a PhD in Computer Science should you wish to continue studying within the subject.

Learning outcomes
-A knowledge of several difference topics in Computer Science at an advanced level.
-An understanding of a body of research literature in Computer Science in your chosen topic, and the underlying principles and techniques of research in this area.
-An ability to engage in independent study at an advanced level, and develop skills in self-motivation and organisation.

Research Project

You will undertake your individual research project over the Summer term and Summer vacation. This will be a culmination of the taught modules you have taken during the course, which will allow you to focus on a specialist area of interest.

You will be allocated a personal supervisor, who will be an expert in your chosen area of research. You will be hosted by the research group of your supervisor, and you will benefit from the knowledge and resources of the whole group. Being attached to a research group also allows you to take part in their informal research seminars, and receive feedback and help from other members of the group.

You can choose from projects suggested by members of our academic staff. You also have the option of formulating your own project proposal, with the assistance from your personal supervisor.

All project proposals are rigorously vetted and must meet a number of requirements before these are made available to the students. The department uses an automated project allocation system for assigning projects to students that takes into account supervisor and student preferences.

The project aims to give you an introduction to independent research, as well as giving you the context of a research group working on topics that will be allied to your own. You will develop the skills and understanding in the methods and techniques of research in Computer Science.

As part of the assessment of the project, as well as your dissertation, you will give a talk about your work and submit a concise paper which we will encourage you to publish.

Information for Students

The MSc in Advanced Computer Science exposes you to several topics in Computer Science that are under active research at York. The material taught is preparatory to helping to continue that research, and perhaps continuing to a PhD. What we require from you are enthusiasm, hard work and enough background knowledge to take your chosen modules.

The modules on the MSc in Advanced Computer Science are mostly shared with our Stage 4 (Masters level) undergraduates. Your technical background will be different, and we acknowledge this.

During August we will send entrants a document describing the background knowledge needed for each module and, in many cases, references to where this knowledge is available (for example, widely available text books and web pages).

More generally, many of the modules expect a high level of mathematical sophistication. While the kind of mathematics used varies from module to module, you will find it useful to revise discrete mathematics (predicate and propositional calculi, set theory, relational and functional calculi, and some knowledge of formal logic), statistics and formal language theory. You should also be able to follow and produce proofs.

Careers

Here at York, we're really proud of the fact that more than 97% of our postgraduate students go on to employment or further study within six months of graduating from York. We think the reason for this is that our courses prepare our students for life in the workplace through our collaboration with industry to ensure that what we are teaching is useful for employers.

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Advanced Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Advanced Computer Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

On the MSc in Advanced Computer Science course you will be thoroughly prepared for a career in IT or related industries. The Advanced Computer Science course is for you if you are a Computer Science graduate or if you have gained experience of computing and programming in a different first degree. Willingness to work hard and an ability to problem solve are equally important for this MSc in Advanced Computer Science. The MSc in Advanced Computer Science course will develop the skills and knowledge you have gained from your first degree by broadening and deepening your knowledge of Computer Science through a variety of advanced modules and material. The MSc in Advanced Computer Science is accredited by the British Computer Society.

Key Features of Advanced Computer Science MSc

• We are top in the UK for career prospects*
• We are 3rd in the UK for teaching quality**
• 5th in the UK overall*
• 7th in the UK for student satisfaction with 98% [National Student Survey 2016]
• 7th in the UK overall and Top in Wales*
• High employability prospects - we are 8th in the UK for graduate prospects*
• 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
• UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
• Our Project Fair allows students to present their work to local industry
• Strong links with industry
• £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)

*Guardian University Guide 2017
**Times & Sunday Times University Guide 2016

Modules of Advanced Computer Science MSc

Modules for the MSc in Advanced Computer Science include Computer Science Project Research Methods but please visit our course page for more information.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

94% of our Postgraduate Taught Graduates of Computer Science were in professional level work or study [DLHE 14/15]

Student Profile

Francesca Madeddu, originally from Italy, completed an outstanding Master’s thesis (which earned her a distinction) investigating interaction with augmented reality on mobile devices. More specifically, she investigated how to interact with virtual Egyptian artefacts placed in real scenes. The final game was deployed at Swansea's Egypt Centre last year and was evaluated by volunteers working at the museum. A Master’s thesis does not often lead to a publication. However, part of Francesca's research was written up as an extended abstract and presented at Computer Graphics and Visual Computing (CGVC), a Eurographics UK conference for visual computing last year. An exceptional achievement!

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Human Computer Interaction at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Human Computer Interaction at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Computer Science is at the cutting edge of modern technology, and is developing rapidly and Swansea Computer Science graduates enjoy excellent employment prospects.

Computer Science now plays a part in almost every aspect of our lives - science, engineering, the media, entertainment, travel, commerce and industry, public services and the home.

The MSc by Research Human Computer Interaction enables students to pursue a one year individual programme of research. The Human Computer Interaction programme would normally terminate after a year. However, under appropriate circumstances, this first year of research can also be used in a progression to Year 2 of a PhD degree.

Students of the MSc by Research Human Computer Interaction programme will be fully integrated into one of our established research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Key Features

The Department of Computer Science is amongst the top 25 in the UK, with a growing reputation in research both nationally and internationally. It is home to world class researchers, excellent teaching programmes and fine laboratory facilities.

All postgraduate Computer Science programmes will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Research

The results of the Research Excellence Framework (REF) 2014 show that we lead Wales in the field of Computer Science and are in the UK Top 20.

We are ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

Read less
Computer Science Departmental degree requirements for the master’s degree, which are in addition to those established by the College of Engineering and the Graduate School (http://graduate.ua.edu/), are as follows for Plan I and Plan II students. Read more
Computer Science Departmental degree requirements for the master’s degree, which are in addition to those established by the College of Engineering and the Graduate School (http://graduate.ua.edu/), are as follows for Plan I and Plan II students.

- Master of Science–Thesis Option (http://cs.ua.edu/graduate/ms-program/#thesis)
- Master of Science–Non-Thesis Option (http://cs.ua.edu/graduate/ms-program/#nonthesis)
- Timetable for the Submission of Graduate School Forms for an MS Degree (http://cs.ua.edu/graduate/ms-program/#timetable)

Visit the website http://cs.ua.edu/graduate/ms-program/

MASTER OF SCIENCE–THESIS OPTION (PLAN I):

30 CREDIT HOURS
Each candidate must earn a minimum of 24 semester hours of credit for coursework, plus a 6-hour thesis under the direction of a faculty member. Unlike the general College of Engineering requirements, graduate credit may not be obtained for courses at the 400-level.

Degree Requirements Effective Fall 2011

Credit Hours
The student must successfully complete 30 total credit hours, as follows:

- 24 hours of CS graduate-level course work

- 6 hours of CS 599 Master’s Thesis Research: Thesis Research.

- Completion of at least one 500-level or 600-level course in each of the four core areas (applications, software, systems and theory). These courses must be taken within the department and selected from the following:
Applications: CS 528, CS 535, CS 557, CS 560, CS 609, CS 615
Software: CS 503, CS 507, CS 515, CS 516, CS 534, CS 600, CS 603, CS 607, CS 614, CS 630
Systems: CS 526, CS 538, CS 567, CS 606, CS 613, CS 618
Theory: CS 500, CS 570, CS 575, CS 601, CS 602, CS 612

- No more than 12 hours from CS 511, CS 512, CS 591, CS 592, CS 691, CS 692 and non-CS courses may be counted towards the coursework requirements for the master’s degree. Courses taken outside of CS are subject to the approval of the student’s advisor.

- Additional Requirements -

- The student will select a thesis advisor and a thesis committee. The committee must contain at least four members, including the thesis advisor. At least two members are faculty of the Computer Science department, and at least one member must be from outside the Department of Computer Science.

- The student will develop a written research proposal. This should contain an introduction to the research area, a review of relevant literature in the area, a description of problems to be investigated, an identification of basic goals and objectives of the research, a methodology and timetable for approaching the research, and an extensive bibliography.

- The student will deliver an oral presentation of the research proposal, which is followed by a question-and-answer session that is open to all faculty members and which covers topics related directly or indirectly to the research area. The student’s committee will determine whether the proposal is acceptable based upon both the written and oral presentations.

- The student will develop a written thesis that demonstrates that the student has performed original research that makes a definite contribution to current knowledge. Its format and content must be acceptable to both the student’s committee and the Graduate School.

- The student will defend the written thesis. The defense includes an oral presentation of the thesis research, followed by a question-and-answer session. The student’s committee will determine whether the defense is acceptable.

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School (http://graduate.ua.edu/) and by the College of Engineering.

Degree Requirements Prior to Fall 2011

Credit hours

The student must successfully complete 30 total credit hours, as follows:

- 6 hours of CS 599 Master’s Thesis Research

- 24 hours of CS graduate-level course work with a grade of A or B, including the following courses completed at The University of Alabama:
At least 3 hours of theory courses (CS 500 Discrete math, CS 601 Algorithms, CS 602 Formal languages, CS 612 Data structures)

At least 3 hours of software courses (CS 600 Software engineering, CS 603 Programming languages, CS 607 Human-computer interaction, CS 614 Compilers, CS630 Empirical Software Engineering)

At least 3 hours of systems courses (CS 567 Computer architecture, CS 606 Operating systems, CS 613 Networks, CS 618 Wireless networks)

At least 3 hours of applications courses (CS 535 Graphics, CS 560 or 591 Robotics, CS 591 Security, CS 609 Databases)

- Additional Requirements -

- The student will select a thesis advisor and a thesis committee. The committee must contain at least four members, including the thesis advisor. At least two members are faculty of the Computer Science department, and at least one member must be from outside the Department of Computer Science.

- The student will develop a written research proposal. This should contain an introduction to the research area, a review of relevant literature in the area, a description of problems to be investigated, an identification of basic goals and objectives of the research, a methodology and timetable for approaching the research, and an extensive bibliography.

- The student will deliver an oral presentation of the research proposal, which is followed by a question-and-answer session that is open to all faculty members and which covers topics related directly or indirectly to the research area. The student’s committee will determine whether the proposal is acceptable based upon both the written and oral presentations.

- The student will develop a written thesis that demonstrates that the student has performed original research that makes a definite contribution to current knowledge. Its format and content must be acceptable to both the student’s committee and the Graduate School.

- The student will defend the written thesis. The defense includes an oral presentation of the thesis research, followed by a question-and-answer session. The student’s committee will determine whether the defense is acceptable.

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School (http://graduate.ua.edu/) and by the College of Engineering.

MASTER OF SCIENCE–NON-THESIS OPTION (PLAN II):

30 CREDIT HOURS
Each candidate must earn a minimum of 30 semester hours of credit for coursework, which may include a 3-hour non-thesis project under the direction of a faculty member. Unlike the general College of Engineering requirements, graduate credit may not be obtained for courses at the 400-level.

Degree Requirements Effective Fall 2011

The student must successfully complete 30 total credit hours, as follows:

- Completion of at least one 500-level or 600-level course in each of the four core areas (applications, software, systems and theory).
Applications: CS 528, CS 535, CS 557, CS 560, CS 609, CS 615
Software: CS 503, CS 507, CS 515, CS 516, CS 534, CS 600, CS 603, CS 607, CS 614, CS 630
Systems: CS 526, CS 538, CS 567, CS 606, CS 613, CS 618
Theory: CS 500, CS 570, CS 575, CS 601, CS 602, CS 612

- No more than 12 hours from CS 511, CS 512, CS 591, CS 592, CS 691, CS 692 and non-CS courses may be counted towards the coursework requirements for the master’s degree. Courses taken outside of CS are subject to the approval of the student’s advisor.

- The student may elect to replace 3 hours of course work with 3 hours of CS 598 Research Not Related to Thesis: Non-thesis Project. This course should be proposed in writing in advance, approved by the instructor, and a copy placed in the student’s file. The proposal should specify both the course content and the specific deliverables that will be evaluated to determine the course grade.

- Additional Requirements -

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School and by the College of Engineering.

Degree Requirements Prior to Fall 2011

Credit hours

The student must successfully complete 30 total credit hours of CS graduate-level course work with a grade of A or B, as follows:

- The following courses will be completed at The University of Alabama:
At least 3 hours of theory courses (CS 500 Discrete math, CS 601 Algorithms, CS 602 Formal languages, CS 612 Data structures)

At least 3 hours of software courses (CS 600 Software engineering, CS 603 Programming languages, CS 607 Human-computer interaction, CS 614 Compilers, CS630 Empirical Software Engineering)

At least 3 hours of systems courses (CS 567 Computer architecture, CS 606 Operating systems, CS 613 Networks, CS 618 Wireless networks)

At least 3 hours of applications courses (CS 535 Graphics, CS 560 or 591 Robotics, CS 591 Security, CS 609 Databases)

- The student may elect to replace 3 hours of course work with 3 hours of CS 598 Research Not Related to Thesis: Non-thesis Project. This course should be proposed in writing in advance, approved by the instructor, and a copy placed in the student’s file. The proposal should specify both the course content and the specific deliverables that will be evaluated to determine the course grade.

- Additional Requirements -

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School and by the College of Engineering.

TIMETABLE FOR THE SUBMISSION OF GRADUATE SCHOOL FORMS FOR AN MS DEGREE
This document identifies a timetable for the submission of all Graduate School paperwork associated with the completion of an M.S. degree

- For students in Plan I students only (thesis option) after a successful thesis proposal defense, you should submit the Appointment/Change of a Masters Thesis Committee form

- The semester before, or no later than the first week in the semester in which you plan to graduate, you should “Apply for Graduation” online in myBama.

- In the semester in which you apply for graduation, the Graduate Program Director will contact you about the Comprehensive Exam.

Find out how to apply here - http://graduate.ua.edu/prospects/application/

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Learning how to make new discoveries that will contribute to a better understanding of the historical, social political and cultural processes that shape societies. Read more

Overview

Learning how to make new discoveries that will contribute to a better understanding of the historical, social political and cultural processes that shape societies.

Are people living in ethnically diverse neighbourhoods more inclined to turn inwards and to ‘hunker down’ compared to people of ethnically homogeneous settings? Are there cross-country differences in the causes of hooliganism, and in the effectiveness of methods used to combat hooligans in different European countries?

More and more comparative questions on societies are being raised. At Radboud University we believe that answers to comparative questions are more informative, lead to a better understanding of societal phenomena and processes, and therefore have more scientific and social importance than answers to questions about one society in one historical period.

This programme therefore fully focuses on teaching students how to perform high-quality comparative research. We look into the degree of inequality, cohesion and modernisation in both Western and non-Western societies. You’ll learn how to translate social problems into empirical research questions and understand the diverse theoretical approaches, research designs, data collections and analyses you need to get the answers you are looking for.

See the website http://www.ru.nl/masters/scs

Why study Social and Cultural Science at Radboud University?

- A majority of our courses are exclusively created and offered for the research students enrolled in this programme, and therefore perfectly match the needs and desires of social and cultural researchers.
- This programme is linked to the Nijmegen Institute for Social and Cultural Research (NISCO) who offer an excellent research environment and have extensive social science databases that students are free to use.
- You’ll participate in group-oriented education and be part of a small, select group of highly motivated national and international students.
- You’ll be given your own workplace (equipped with a computer) in a room with your fellow students to enhance solidarity. Every student also receives personal guidance and supervision.
- You’ll write two scientific journal papers which will not only give you plenty of practise but will also give you a good academic research portfolio that you can use when applying for research positions.
- A large majority of our graduates gain PhD and other research positions; almost all of our graduates found work shortly after graduating.

Multidisciplinary

The programme combines the disciplines of sociology, anthropology, development studies and communication science. This programme is therefore ideal for Bachelor’s students from these disciplines with an interest in research. However, we believe that students from disciplines such as political science, economics and human geography can also profit from this Master’s.

The Research Master’s in Social and Cultural Science trains aspiring researchers and is ideal preparation for PhD positions or research positions in relevant non-academic research institutes. Or you could build a bridge between academic research and the world of practice, thereby influencing policy-making in the public and private sphere.

Quality label

This programme was recently awarded the quality label ‘Top Programme' in the Netherlands in the Keuzegids Masters 2015 (Guide to Master's programmes).

Career prospects

The career prospects of a graduate of Social and Cultural Science are good; almost 100% of our alumni found a job or research position immediately after graduating.

Job positions

There are plenty of options open to graduates of the research Master’s in Social and Cultural Science:
- Scientific research career (academia)
The programme provides an excellent basis for a scientific research career and attaining PhD positions.

- Societal research career
Our graduates can also go on to have careers in relevant non-academic research and policy institutes like government ministries, Statistics Netherlands (CBS), The Netherlands Institute for Social Research (SCP) and The Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and foreign equivalents.

- More
Of course, this Master’s programme does not close other doors. Students with a research Master’s are also highly sought after by (commercial) businesses and organisations because of their analytical and communication skills and in-depth understanding of social and cultural behaviour. Other careers, such as policymaker, manager, journalist, etc are certainly within reach.

Find information on Scholarships here http://www.ru.nl/scholarships

See the website http://www.ru.nl/masters/scs

Our research in this field

Half of the Master’s programme in Social and Cultural Science consists of practical research training.

In the first year, you’ll do a research project in which you conduct a small-scale empirical research under guided supervision of a senior researcher. The comparative research issue is typically part of the ongoing research within a Radboud chair group. Finally, you’ll write a scientific journal paper regarding the research results. The project is done in small groups (2-3 students) and prepares you well to independently conduct a comparative empirical social science study for your Master’s thesis in the second.

- Master’s thesis topics in the field of Social and Cultural Science
For your Master’s thesis you are completely free to tackle any social issue in the disciplines of sociology, anthropology, communication science or development studies. Important is the ability to reflect on the societal significance of your research question and the societal importance of your research. Thesis topics vary widely:
- Many theses are concerned with cross-country comparisons of behaviour or attitude measures using European cross-sectional survey data on, for example, xenophobia or gender roles.
- Others theses compare classrooms and the effect ethnic composition has on interethnic bullying or the impact of the economic crisis on African migrants in Athens, Greece, or the utilisation of different sexual health services by Aboriginal adolescents.
- Thesis topics can also be found in the field of communication science, like examining the news on extreme right political parties in Belgium, Germany and the Netherlands and correlating it with election results, or studying patterns in TV drama (e.g. increasing Americanisation) and comparing these media trends with societal processes such as individualisation.

See the website http://www.ru.nl/masters/scs

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The Department of Computer Science at Binghamton University aims to provide all graduates with a strong foundation in computer science while also offering the opportunity to pursue specific interests within computer science and/or interests in other disciplines. Read more
The Department of Computer Science at Binghamton University aims to provide all graduates with a strong foundation in computer science while also offering the opportunity to pursue specific interests within computer science and/or interests in other disciplines. The program provides students with an understanding of the theory and practice of automating the representation, storage and processing of information, while emphasizing experimental research to design and engineer a wide variety of computer and information systems.

The Master of Science in Computer Science (MSCS) is intended for students with a strong background in computer science and a desire to prepare for research studies or professional practice. If you have bachelor's degree in computer science or a related field, you're invited to apply for admission to our MSCS program.

The doctoral program leads to a PhD in Computer Science. Students admitted into the program typically have a master's degree in computer science or a closely related discipline. Students with a bachelor's degree and a strong academic record may also be directly admitted.

Recent doctoral graduates have gone on to careers in as software engineering at Intel, eBay, Cisco Systems, positions at Hewlett Packard, Microsoft, Twitter, Bloomberg, the Air Force Research Lab, and the U.S. Census. Academic placements include assistant professorships at California State University at Fullerton, Valdosta State University, and Harran University, Turkey.

The Master's program leads to a Master of Science in Computer Science. It is intended for students with a strong background in computer science and a desire to prepare for research studies or professional practice. Holders of the baccalaureate degree in computer science or a related field are invited to apply for admission to the MSCS program. Students whose undergraduate degree is not in computer science may be required to complete some preparatory work in addition to fulfilling the requirements listed below.
Program requirements include four core courses taken over the first two semesters of study. These courses are Computer Organization and Architecture, Operating Systems, Programming Languages and Design & Analysis of Computer Algorithms. Three graduating options are offered: a thesis option, a project option and a comprehensive exam. Beyond the 4 core courses, these options require students to complete 4, 5 and 6 elective courses, respectively, chosen from a broad set of courses offered by the Department.

Applicant Qualifications

- Undergraduate major in computer science or related field desirable for admission
- Applicants are additionally expected to have completed coursework in the following areas:
*Algorithms and data structures
*Computer organization and architecture
*Operating systems
*Programming languages
*Discrete mathematics

All applicants must submit the following:

- Online graduate degree application and application fee
- Transcripts from each college/university you have attended
- Two letters of recommendation (three letters of recommendation for PhD applicants)
- Personal statement (2-3 pages) describing your reasons for pursuing graduate study, your career aspirations, your special interests within your field, and any unusual features of your background that might need explanation or be of interest to your program's admissions committee.
- Resume or Curriculum Vitae (max. 2 pages)
- Official GRE scores

And, for international applicants:
- International Student Financial Statement form
- Official bank statement/proof of support
- Official TOEFL, IELTS, or PTE Academic scores

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* Subject to validation, 2017 entry. Liverpool Hope’s MSc Computer Science is a research-informed, academically rigorous course and is designed to provide a flexible, purposeful and challenging set of coherent courses to meet scientific, industrial and employment challenges in this fast-evolving technological area. Read more
* Subject to validation, 2017 entry

Liverpool Hope’s MSc Computer Science is a research-informed, academically rigorous course and is designed to provide a flexible, purposeful and challenging set of coherent courses to meet scientific, industrial and employment challenges in this fast-evolving technological area. Graduates will have developed scientific and analytical skills which are highly valued in the computing, engineering, IT and business industries.

The course offers a mix of compulsory and elective courses, and a research dissertation, so you can focus your skill base and your potential career direction.

The course has been designed with employability in mind, whether it is within IT industry or as a function of other sectors, scientific computing and technical skills are in great demand and therefore highly valued. There are opportunities for placements and enterprise development.

Curriculum

The MSc Computer Science combines academic and practical course, consisting of eight taught courses (four compulsory and four elective) and a dissertation (final research project).

The Compulsory courses are:

· Computational Modelling and Simulation

· Algorithms

· Innovations in Computer Science

· Research Methods for Computer Science

· Dissertation for MSc Computer Science

Elective courses include:

· Embedded Systems and Robotics

· Cloud Computing and Web Services

· Mobile and Ubiquitous Computing

· Human Computer Interaction

· E-Business

Course Descriptions

· Computational Modelling and Simulation (compulsory – 15 credits): This course develops understanding and knowledge of the principles, techniques and design of computational modelling and their applications.

· Algorithms (compulsory - 15 credits): This course gives a firm grounding in the philosophy and evolution of algorithmic design and analysis for computer science, engineering and information systems.

· Innovations in Computer Science (compulsory - 15 credits): You will examine the particular research interests of Computer Science Department.

· Research Methods for Computer Science (compulsory - 15 credits): The course will expose you to the established techniques of research and enquiry that are used to extend, create and interpret knowledge in computer science

· Embedded Systems and Robotics (elective - 15 credits): This course will examine the Robotics Operating System and robotic programming languages, such as Urbi.

· Cloud Computing and Web Services (elective - 15 credits): You will study the concepts behind the idea of cloud computing and web services and gain practical knowledge of Azure, the .Net framework and C#.

· Mobile and Ubiquitous Computing (elective - 15 credits): You will examine mobile phone OSs (Android) and Windows Phone 7. You will learn how to develop software for these devices using JavaFX and C#/Silverlight.

· Human Computer Interaction (elective - 15 credits): Human computer interaction (HCI) is the study of interaction between people and computers and is the most multi-disciplinary module available in the MSc Computer Science.

·
* E-Business (elective - 15 credits): E-business encompasses, and is more than, e-commerce. You will examine e-commerce technology, such as the internet and web-based technologies.

· Dissertation for MSc Computer Science (compulsory - 60 credits): This module will allow the students to develop a Masters level research project with the support of an academic supervisor.

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Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE). Read more
Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE). As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The LSI programme is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics.

As a graduate of the LSI programme you will:
-Have first class knowledge and capabilities for a career in life science research and in expert duties in the public and private sectors.
-Competence to work as a member of a group of experts.
-Have understanding of the regulatory and ethical aspects of scientific research.
-Have excellent communication and interpersonal skills for employment in an international and interdisciplinary professional setting.
-Understand the general principles of mathematical modelling, computational, probabilistic and statistical analysis of biological data, and be an expert in one specific specialisation area of the LSI programme.
-Understand the logical reasoning behind experimental sciences and be able to critically assess research-based information.
-Have mastered scientific research, making systematic use of investigation or experimentation to discover new knowledge.
-Have the ability to report results in a clear and understandable manner for different target groups.
-Have good opportunities to continue your studies for a doctoral degree.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.

Algorithmic Bioinformatics
Goes with the Genome-scale algorithmics, Combinatorial Pattern Matching, and Practical Algorithms and Data Structures on Strings research groups. This specialisation area educates you to be an algorithm expert who can turn biological questions into appropriate challenges for computational data analysis. In addition to the tailored algorithm studies for analysing molecular biology measurement data, the curriculum includes general algorithm and machine learning studies offered by the Master's Programmes in Computer Science and Data Science.

Applied Bioinformatics
Jointly with The Institute of Biotechnology and genetics. Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.

Biomathematics
With the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group.

Biostatistics and Bioinformatics
Offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational Genetics, Computational Genomics and Computational Systems Medicine in FIMM. Topics and themes include statistical, especially Bayesian methodologies for the life sciences, with research focusing on modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of collaborative topics in various biomedical disciplines. In particular, research and teaching address questions of population genetics, phylogenetic inference, genome-wide association studies and epidemiology of complex diseases.

Eco-evolutionary Informatics
With ecology and evolutionary biology, in which several researchers and teachers have a background in mathematics, statistics and computer science. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Evolutionary biology studies processes supporting biodiversity on different levels from genes to populations and ecosystems. These sciences have a key role in responding to global environmental challenges. Mathematical and statistical modelling, computer science and bioinformatics have an important role in research and teaching.

Systems Biology and Medicine
With the Genome-scale Biology Research Program in Biomedicum. The focus is to understand and find effective means to overcome drug resistance in cancers. The approach is to use systems biology, i.e., integration of large and complex molecular and clinical data (big data) from cancer patients with computational methods and wet lab experiments, to identify efficient patient-specific therapeutic targets. Particular interest is focused on developing and applying machine learning based methods that enable integration of various types of molecular data (DNA, RNA, proteomics, etc.) to clinical information.

Selection of the Major

During the first Autumn semester, each specialisation area gives you an introductory course. At the beginning of the Spring semester you are assumed to have decided your study direction.

Programme Structure

Studies amount to 120 credits (ECTS), which can be completed in two years according to a personal study plan.
-60 credits of advanced studies from the specialisation area, including a Master’s thesis, 30 credits.
-60 credits of other studies chosen from the programme or from other programmes (e.g. computer science, mathematics and statistics, genetics, ecology and evolutionary biology).

Internationalization

The Life Science Informatics MSc is an international programme, with international students and an international research environment. The researchers and professors in the programme are internationally recognized for their research. A significant fraction of the teaching and research staff is international.

As a student you can participate in an international student exchange programme, which offers the possibility to include international experience as part of your degree. Life Science Informatics itself is an international field and graduates can find employment in any country.

In the programme, all courses are given in English. Although the Helsinki region is very international and English is widely spoken, you can also take courses to learn Finnish via the University of Helsinki’s Language Centre’s Finnish courses. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning new languages.

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Our highly sought-after graduates benefit from a programme that integrates training in identifying, framing and effectively researching social problems with a leading computational approach to social science. Read more
Our highly sought-after graduates benefit from a programme that integrates training in identifying, framing and effectively researching social problems with a leading computational approach to social science.

Furthermore, we are home to the Centre for Research in Social Simulation (CRESS) and its world-leading expertise in agent-based modelling.

PROGRAMME OVERVIEW

Interest in simulation has grown rapidly in the social sciences. New methods have been developed to tackle this complexity. This programme will integrate traditional and new methods, to model complexity, evolution and the adaptation of social systems.

These new methods are having an increasing influence on policy research through a growing recognition that many social problems are insufficiently served by traditional policy modelling approaches.

The Masters in Social Science and Complexity will equip you to develop expertise in the methods necessary to tackle complex, policy-relevant, real-world social problems through a combination of traditional and computational social science methods, and with a particular focus on policy relevance.

PROGRAMME STRUCTURE

This programme is studied full-time over one academic year and part-time over two academic years. It consists of eight taught modules and a dissertation. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Data Analysis
-Field Methods
-Computational Modelling
-Theory Model Data
-Modelling the Complex World
-Policy Modelling
-Theory and Method
-Statistical Modelling
-Evaluation Research
-Dissertation

EDUCATIONAL AIMS OF THE PROGRAMME

The main aims of the programme are to:
-Provide an appropriate training for students preparing MPhil/PhD theses, or for 
 students going on to employment involving the use of social science and policy research
-Provide training that fully integrates social science, policy modelling and computational methodologies to a high standard
-Provide training resulting in students with high quality analytic, methodological, computational and communication skills

PROGRAMME LEARNING OUTCOMES
The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:
-Develop skills in tackling real world policy problems with creativity and sound methodological judgment
-Cover the principles of research design and strategy, including formulating research 
questions or hypotheses and translating these into practicable research designs and models
-Introduce students to the methodological and epistemological issues surrounding research in the social sciences in general and computational modelling in particular
-Develop skills in programming in NetLogo for the implementation of agent-based models for the modelling of social phenomena
-Develop skills in the acquisition and analysis of social science data
-Make students aware of the range of secondary data available and equip them to evaluate its utility for their research
-Develop skills in searching for and retrieving information, using library and Internet resources
-Develop skills in the use of SPSS, and in the main statistical techniques of data analysis, including multivariate analysis
-Develop skills in the use of CAQDAS software for the analysis of qualitative data
-Develop skills in writing, in the preparation of a research proposal, in the presentation ofresearch results and in verbal communication
-Help students to prepare their research results for wider dissemination, in the form of seminar papers, conference presentations, reports and publications, in a form suitable for a range of audiences, including academics, stakeholders, policy makers, professionals, service users and the general public

Knowledge and understanding
-Show advanced knowledge of qualitative, quantitative and computational methodologies in the social science
-Show advanced knowledge of modelling methodologies, model construction and analysis
-Show critical understanding of methodological and epistemological challenges of social science and computer modelling
-Show critical awareness and understanding of the methodological implications of a range of sociological theories and approaches
-Show understanding the use and value of a wide range of different research approaches across the quantitative and qualitative spectra
-Show advanced knowledge in data collection, analysis and data driven modelling
-Show advanced knowledge of policy relevant social science research and modelling
-Show advanced understanding of the policy process and the role of social science and modelling therein
-Show advanced knowledge of statistical modelling

Intellectual / cognitive skills
-Systematically formulate researchable problems; analyse and conceptualise issues; critically appreciate alternative approaches to research; report to a range of audiences
-Conceptual development of Social Science and Complexity models to creatively enhance the understanding of social phenomena
-Integration of qualitative, quantitative and computational data
-Judgement of problem-methodology match
-Analyse qualitative and quantitative data drawn both from ‘real world’ and ‘virtual world’ environments, using basic and more advanced techniques, and draw warranted conclusions
-Develop original insights, questions, analyses and interpretations in respect of research questions
-Critically evaluate the range of approaches to research

Professional practical skills
-Formulate, design, plan, carry out and report on a complete research project
-Use the range of traditional and computational techniques employed in sociological research
-Ability to produce well founded, data driven and validated computational models
-Generate both quantitative and qualitative data through an array of techniques, and select techniques of data generation on appropriate methodological bases
-Employ a quantitative (SPSS) and qualitative software package to manage and analyse data
-Plan, manage and execute research as part of a team and as a sole researcher
-Ability to communicate research findings models in social science and policy relevant ways
-Ability to manage independent research

Key / transferable skills
-Communicate complex ideas, principles and theories by oral, written and visual means
-Apply computational modelling methodology to complex social issues in appropriate ways
-Creativity in approaching complex problems and a the ability of communicating and justifying problem solutions
-Apply computing skills for computational modelling, research instrument design, data analysis, and report writing and presentation
-Work to deadlines and within work schedules
-Work independently or as part of a team
-Demonstrate experience of a work environment

PLACEMENTS

On the MSc Social Science and Complexity, we offer the opportunity to take a research placement during the Easter vacation. This will provide you with first-hand experience of real-life policy research in action.

Organisations in which placements might be possible are a number of consultancies (e.g. Sandtable), government departments (e.g. Defra) and academic research centres (e.g. Centre for Policy Modelling at Manchester).

CAREER OPPORTUNITIES

Computational methods and especially computer-based simulations, are becoming increasingly important in academic social science and policy making.

Graduates might find career opportunities in government departments, consultancies, government departments, consultancies, NGOs and academia.

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

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The College of Social Sciences welcomes all postgraduates to the recently redesigned MA in Social Research programme which continues to enjoy full RT (research training) recognition by the Economic and Social Research Council (ESRC). Read more
The College of Social Sciences welcomes all postgraduates to the recently redesigned MA in Social Research programme which continues to enjoy full RT (research training) recognition by the Economic and Social Research Council (ESRC). This programme aims to provide students with a sound background in social research design and the most up-to-date training in methods of data collection and analysis. The combination of core modules and short courses on more advanced topics provides maximum flexibility for taught postgraduate and research students throughout their study.

The core elements of the programme are delivered by staff across the entire College, many of whom are engaged in cutting-edge research in their own fields. Students will benefit by undertaking the modules with others from different departments within the School of Government and Society, eg, Political Science and International Studies; the Centre for Russian and East European Studies; the Institute for Applied Social Studies; and within the wider College. Students will also receive training on more discipline-specific research elements, as well as dissertation supervision, provided by individual departments. On completion of this MA, many students continue their PhD studies or pursue a career in research in the public, private or voluntary sector.

Programme content
Term 1:

Introduction to Social Research (20)
Research Design (20)
Thesis-related preparation
Information Skills for Social Sciences
University Programme of Skills Training (as necessary)
Dissertation-related preparation
Term 2:

Social Research Methods I (20)
Social Research Methods II (20)
Thesis-related preparation
Summer Term:

Four Short courses (10)
Dissertation (60)
All students registered on the MA in Social Research will take:

1) Four core modules:

Introduction to Social Science Research (20 credits)
Research Design (20 credits)
Social Research Methods I (20 credits)
Social Research Methods II (20 credits)


2) Four elective modules (10 credits each) from the short course programme below
3) A 14,000 word dissertation (60 credits)

Short courses
All short courses run as 2-day intensive workshops from 10–4pm with breaks. This list is updated regularly as new courses are approved so do check this website from time to time to see what is on offer.

These short courses are open to all research students in the College (and some departments in other Colleges, such as Geography, subject to the discretion of the Programme Team). However, places on each course are limited and priority will be given to MA Social Research students.

These short courses are also open to all staff in the University who may wish to attend without completing the assessments. However, all doctoral researchers and staff who wish to to so will be placed on a waiting list. Confirmation will be sent a week before the course dates.

Short course programmes
From Multiple linear to Logistic regression
Narrative Research
Analyzing Hierarchical and Panel Data
Visual Research Methods
Linguistic Ethnography
Documentary Research in Education, History and the Social Sciences
Researching Disability
Approaches to Research on Discourse
Policy Evaluation
Advanced Qualitative Data Analysis (using NVivo)
Secondary Research Data Analysis in Social Research
Applications of Geographic Information Systems in Social Science
Overseas Research
Q Methodology – A Systematic Approach for Interpretive Research Design
Activity Theory and its research applications
Some courses have pre-requisites, eg, to register on Multiple Linear and Logistic Regression, Factor Analysis and Narrative Research; you will need to have passed Data Analysis (20 credits module) or equivalent. For the latter, you will need to provide evidence that you have passed a similar course on quantitative/qualitative data analysis where appropriate.

Please be aware that some of these courses run on the same dates. Make sure you have not picked courses that clash with each other. For further details or to sign up for these short courses, please email the course names, your name, student ID and your programme to |.

Skills and attributes gained
Students will have acquired a solid foundation of a broad range of research methods that are widely used in the social sciences and will have developed:

A sound understanding of the methodological debates
An overview of the philosophy of social science and how this informs research design, methods chosen of data collection and analysis
An ability to use a range of research techniques appropriate to their subject area
Competence in the representation and presentation of information and data
An ability to communicate research findings effectively to a wider range of audiences
An appreciation of the potential use and impact of their research within and beyond academia
An ability to engage with relevant users at all points in the research process, from devising and shaping research questions through to enhancing practice
Learning and teaching
Students are expected to engage in high-level discussion during all sessions. Teaching will be delivered by a combination of lectures, seminars and computer workshops. Some fieldwork involving primary data collection is required where appropriate.

Careers
Many students go on to do a PhD after completing this MA. Others have followed a career in local authorities, government departments, health authorities, management consultancy, media, the voluntary sector and so on.

Assessment
All core modules are assessed by a 4000-word essay or report. On most short courses, a 3000-report is usually required. The dissertation length is 14,000 words and students are expected to utilise the knowledge and skills they learned from the taught elements in this programme.

Explore postgraduate study at Birmingham at one of our on-campus open days (Friday 13 November 2015 and Friday 4 March 2016). Register to attend at: http://www.birmingham.ac.uk/postgraduate/visit

If you can’t make it to one of our on-campus open days, our virtual open days run regularly throughout the year. For more information, please visit: http://www.pg.bham.ac.uk

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