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Masters Degrees (Computer Science Research)

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This two-year master’s programme Computer Science offers stimulating, significant and innovative research at an internationally renowned institute and combines theoretical, experimental and applied approaches. Read more

This two-year master’s programme Computer Science offers stimulating, significant and innovative research at an internationally renowned institute and combines theoretical, experimental and applied approaches.

What does this master’s programme entail?

The two-year master’s programme in Computer Science offers six specialisations which combine excellent theoretical teaching with possibilities for applied work with industrial relevance. This is achieved by intensive collaboration with companies at the Leiden Centre of Data Science. Course themes include topics such as Evolutionary Algorithms, Neural Networks, Databases and Data Mining, Swarm-Based Computation, Bayesian Networks, Multimedia Systems, Embedded Systems and Software, Advanced Compilers and Architectures, Bio-Modeling and Petri Nets.

Read more about our Computer Science programme.

Why study Computer Science at Leiden University?

  • Interdisciplinary research opportunities as well as industrial applications provide you with exciting possibilities. The industrial application areas and interdisciplinary activities include, among others: Bioinformatics and Life Sciences, Medicine, Pharma, Physics, Engineering Applications, Logistics Applications, Energy and Utility related Applications and Financial Applications.
  • You will benefit from our diverse collaborations and the possibilities for internships and projects with our partners such as BMW, ING and Strukton.
  • You have ample of opportunities to assemble your own study path: an individually tailored programme will be designed for each student.

Find more reasons to choose Computer Science at Leiden University.

Computer Science: the right master’s programme for you?

The programme is open for students with an internationally recognized bachelor’s degree in computer science or equivalent. You will be trained as an independent researcher, equipped with the necessary skills to advance your career as a computer scientist.

Read more about the entry requirements for Computer Science.

Specialisations



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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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About the program. The Bond University Master of Sports Science is designed to develop specialist knowledge and skills relating to strength and conditioning and high performance science of elite athletes. Read more

About the program

The Bond University Master of Sports Science is designed to develop specialist knowledge and skills relating to strength and conditioning and high performance science of elite athletes.

The program is suitable for graduates in exercise and sports science aspiring for a career in high performance sport, or for established professionals such as domestic and international strength and conditioning coaches, or high performance managers seeking professional updates.

This unique program places a strong emphasis on comprehensive practical experience and industry immersion, including a two semester full-time professional internship under the mentorship of a sports scientist.

Completed in only 1 year and 4 months (4 semesters), the first two semesters are comprised of specialist on-campus coursework, followed by the internship which incorporates applied sports science /strength and conditioning practice and a research component. This component is undertaken within a professional or semi-professional sporting organisation with whom Bond University has agreements for student internships. Alternatively, students may elect to undertake their internship with an external organisation or employer relative to their field of work, with prior approval from Bond University.  

The program will culminate with the submission of a peer-reviewed manuscript that may be eligible for publication, providing an additional pathway for you to progress to further postgraduate research.

The program provides you with exposure to authentic high performance sports science learning both on campus and in industry. The coursework component is delivered primarily at the world-class Bond Institute of Health & Sport, where you will gain exceptional, high-quality practical experience in our high performance gym, health science laboratories and sports science research laboratories. You will have access to specialised technology used in research to deliver a wide range of athlete testing and performance analysis. These facilities provide sports science testing and training services to a variety of elite and sub-elite athletes, providing an exceptional learning experience. 

Professional outcomes

The Master of Sports Science will enable you to apply knowledge and practical experience in high performance sports science across all levels of national and international sport.

Possible career opportunities include, but are not limited to:

  • Sports Scientist/ Strength and Conditioning Specialist positions in professional sport, working with teams or individual athletes
  • Sports Scientist/ Strength and Conditioning Specialist positions in national and international sporting organisations
  • Development officer for professional sporting and health orientated organisations
  • Corporate and community health and fitness consultant
  • Health promotion/ lifestyle consultant
  • Athletic/ sports program coordinator

Successful graduates may be eligible to progress to further post graduate research, leading to potential career options in research organisations and academia.

Structure and subjects

The Master of Sports Science consists of a specialised coursework and integrated research and internship model.

You must complete all of the following subjects:

Semester 1

Semester 2

Semester 3

Semester 4

*Subject names and structure may change 

Teaching methodology

The Master of Sports Science program uses a teaching methodology that involves a combination of lectures, tutorials, seminars, examinations, projects, presentations, assignments, computer labs and industry projects. Examination formats may include objective structure practical examinations, theory papers, assignments and oral presentations. The program will culminate with the submission of a peer-reviewed manuscript that may be eligible for publication. 

During coursework, you will be primarily located at the Bond Institute of Health and Sport, within the Cbus Stadium sporting precinct at Robina.

Internship and research

A unique feature of this program is the completion of an integrated professional placement and internship, under the mentorship of a sports scientist. This internship is completed full-time for 2 semesters, at a minimum of 500 hours with an elite sport organisation.

Bond University has affiliations with national and international elite sporting organisations and professional sports teams.

* Students intending to apply should be aware of the following: You may be required to attend internships with organisations in locations other than the Gold Coast region.These placements may involve additional associated costs (i.e. accommodation and travel) for which you will be responsible.

Research

Bond University has a burgeoning profile in health and sports science research. Major investment in infrastructure including the ‘Bond Institute of Health and Sport’ have fostered collaborations between ‘bench top’ scientists and practitioners, providing opportunities for innovative research.

Bond University is the lead institution for the Collaborative Research Network (CRN) for Advancing Exercise and Sports Science CRNAESS). The CRN-AESS brings together partners from key research and sports science institutions including the Australian Institute of Sport building research capacity and excellence in exercise and sports science, human genetics and bioinformatics, to better understand health, human performance and injury management.



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science. Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science: Informatique at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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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A core feature of the degree is the development of independent research skills, including the collection and analysis of data and critical review of the relevant literature. Read more

A core feature of the degree is the development of independent research skills, including the collection and analysis of data and critical review of the relevant literature.

The MSc(Research) normally takes two years of full-time study to complete, but you have the option to complete on a part-time basis.  In the first year you will complete 120 points of taught papers with the second year spent doing a 120 point research thesis.

Study an MSc(Research) at Waikato University and you will enjoy more lab and field work, more one-on-one time with top academics and access to world-class research equipment. Our great industry contacts will also mean exciting collaborations with local, national and international companies and organisations.

Facilities

The University of Waikato’s School of Science is home to a suite of well-equipped, world-class laboratories.  You will have the opportunity to use complex research equipment and facilities such as NMR spectroscopyDNA sequencing and the University of Waikato Herbarium.

The computing facilities at the University of Waikato are among the best in New Zealand, ranging from phones and tablets for mobile application development to cluster computers for massively parallel processing. Students majoring in Computer Science, Mathematics and Statistics will have 24 hour access to computer labs equipped with all the latest computer software.

Practical experience

You will spend more time putting theory into practice in the laboratories and out in the field. Smaller class sizes in taught papers mean more one-on-one time with renowned academics.

The University of Waikato also boasts excellent industry collaborations with organisations such as NIWA, AgResearch, Plant and Food Research and Landcare Research. These strong relationships generate numerous research projects for MSc(Research) students, who are able to work on real issues with a real client.

Subjects

Students enrolling in an (MSc(Research) via the Faculty of Science & Engineering can study Biological SciencesChemistryEarth SciencesElectronicsEnvironmental SciencesMaterials and ProcessingPhysics or Psychology.

Students taking  Computer ScienceMathematics or Statistics will enrol through the Faculty of Computing & Mathematical Sciences.

Career opportunities

  • Local and Regional Council
  • Crown Research Institutes
  • Energy Companies
  • Environmental Agencies
  • Government Departments
  • Biomedical/Pharmaceutical Industries
  • Private Research Companies
  • Food and Dairy Industries
  • Agriculture and Fisheries


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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Advanced Computer Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Advanced Computer Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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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This programme provides practical, career-orientated training in social science research methods, including research design, data collection and data analysis relating to both qualitative and quantitative modes of inquiry. Read more

This programme provides practical, career-orientated training in social science research methods, including research design, data collection and data analysis relating to both qualitative and quantitative modes of inquiry.

Students will have the opportunity to specialise in particular methodologies and to learn more about the application of these methodologies to illuminate important issues and debates in contemporary society.

Course Details

The programme is designed to provide a fundamental grounding in both quantitative and qualitative research skills, along with the opportunity to specialise in more advanced training in quantitative research, qualitative research or in practical applications of research techniques.

CORE MODULES:

Semester 1

Approaches to Social Research (20 CATS)

This module offers an introduction to the different styles of social science research as well as guidance and illustrations of how to operationalize research questions and assess them empirically. Students will be shown how to conduct systematic literature searches and how to manage empirical research projects. The module will also explore issues around the ethics of social science research as well as the connection between social science research and policy concerns. It is designed as preparation for undertaking postgraduate research and dissertation work.

Theory and Debates in Social Research (20 CATS)

This module aims to deepen students' understanding of key debates in social theory and research, providing advanced level teaching for those building upon basic knowledge and undertaking postgraduate research. It is designed to demonstrate and explore how social theory is utilised, critiqued and developed through the pursuit of social science research.

The Sources and Construction of Qualitative Data (10 CATS)

The purpose of this module is to illuminate the theoretical underpinnings of qualitative research. The module will discuss the impact of various theories on the nature and conduct of qualitative research particularly around questions of epistemology and ontology. The role of different types of interviewing in qualitative research will be utilised in order to explore the relationship between theory and methods.

The Sources and Construction of Quantitative Data (10 CATS)

The aim of the module is to provide a comprehensive overview of the theory and practice of measurement and constructing quantitative data in the social sciences. Through lectures and practical exercises, this module will provide students with relevant knowledge of secondary data sources and large datasets, their respective uses and usefulness, and their relevance for the study of contemporary social issues

Semester 2

Qualitative Data Analysis (10 CATS)

The module will provide students with an overview of different approaches to qualitative data analysis. It will include introductory training to this skill that includes such techniques as thematic analysis and discourse analysis, as well as computer assisted qualitative data analysis. It will provide the knowledge necessary for the informed use of the qualitative data analysis software package NVivo. The module gives students a base level introduction to the analytical and technical skills in qualitative data analysis appropriate to the production of a Master's dissertation and/or use of CAQDAS software for social science research purposes.

Quantitative Data Analysis: Foundational (10 CATS)

This module provides an introduction to the basics of quantitative data analysis. The module will begin with a brief review of basic univariate and bivariate statistical procedures as well as cover data manipulation techniques. The module is taught through a series of seminars and practical workshops. These two strands are interwoven within each teaching session. Please note that students may be granted an exemption from this module if they have already successfully completed a module that has the equivalent learning outcomes.

Quantitative Data Analysis: Intermediate (10 CATS)

This module advances students' confidence and knowledge in the use of SPSS. The module focuses on multivariate regression models, including the appropriate use and awareness of statistical assumptions underlying regression and the testing and refinement of such models.

Dissertation (60 CATS)

A dissertation of no more than 15,000 words on a topic relevant to social science research methods training. The thesis will involve either carrying out and reporting on a small social science research project which includes a full and considered description and discussion of the research methods employed or the discussion of a research issue or technique to a level appropriate for publication.

OPTIONAL MODULES (all 10 CATS)

We offer a range of advanced modules in quantitative and qualitative research methods, for example, logistic regression, internet-based research and visual research methods. We also provide specialist modules which reflect the teaching team’s diverse research interests, from the social logic of emotional life to conflict and change in divided societies. Optional modules generally run during the Spring semester and are offered subject to sufficient student demand and staff availability. Students will be able to choose a maximum of three to four option modules (depending on whether they need to complete Quantitative Data Analysis: Foundational). Please note that it is unlikely that all the following modules will be available for 2017/8. Please check with the Programme Director for queries about specific modules.

  • Advanced Qualitative Research Methods
  • Social Science Research Online
  • Visual Research Methods
  • Longitudinal Analysis
  • Advanced Quantitative Research Methods
  • Conflict and Change in Northern Ireland: New Sociological Research
  • Researching Emotions and Social Life
  • University Research and Civil Society Organisations


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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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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Human Computer Interaction at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Human Computer Interaction at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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*).



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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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The UCL programme in Data Science for Research in Health and Biomedicine covers computational and statistical methods as applied to problems in data-intensive medical research. Read more

The UCL programme in Data Science for Research in Health and Biomedicine covers computational and statistical methods as applied to problems in data-intensive medical research. Students learn techniques that are transforming medical research and creating exciting new commercial opportunities. Our recent graduates, many of whom begin paid internships while completing the MSc, have moved on to roles in industry and academia.

About this degree

Students learn how to link and analyse large complex datasets. They design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The content is drawn from epidemiology, computer science, statistics and other fields, including genetics.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits) and a dissertation/report (60 credits).

A Postgraduate Diploma (120 credits) is offered.

A Postgraduate Certificate (60 credits) is offered.

Core modules

  • Principles of Epidemiology Applied to Electronic Health Records Research
  • Data Management for Health Research
  • Statistics for Epidemiology and Public Health
  • Statistical Methods in Epidemiology
  • Topics in Health Data Science

Optional modules

  • Advanced Statistics for Records Research
  • Database Systems
  • Information Retrieval and Data Mining
  • Principles of Health Informatics
  • Machine Learning in Healthcare and Biomedicine
  • Statistics for Interpreting Genetic Data
  • Electronic Health Records
  • Clinical Decision Support Systems

Dissertation/report

All students undertake an independent research project which culminates in a dissertation. Project Proposal 20% (2,000 words); Journal Article 80% (6,000 words).

Teaching and learning

The programme is delivered by clinicians, statisticians and computer scientists from UCL, including leading figures in data science. We use a combination of lectures, practical classes and seminars. A mixture of assessment methods is used including examinations and coursework.

Further information on modules and degree structure is available on the department website: Data Science for Research in Health and Biomedicine MSc

Careers

Students on this programme will be passionate about research and know that, in the 21st century, some of the most exciting, stimulating and productive research is carried out using large collections of data acquired in big collaborative endeavours or major public or private initiatives. We hope that graduates will build on that passion and, together with the experience gained on the programme, will go one to develop careers as entrepreneurs, scientists and managers, working in industry, academia and healthcare.

Employability

The programme is designed to meet a need, identified by the funders of health research and by a number of industrial organisations and healthcare agencies, for training in the creation, management and analysis of large datasets. This programme is practical, cross-disciplinary and closely linked to cutting-edge research and practice at UCL and UCL’s partner organisations. Data science is arguably the most rapidly growing field of employment at the moment and employers recruiting in health data science include government agencies, technology companies, consulting and research firms as well as scientific organisations. A number of employers are supporting the programme in different ways, including providing paid internships to selected students.

Why study this degree at UCL?

Data science is an exciting area with a dynamic job market, including in healthcare. Our graduates have gone on to work for a range of companies, including large research organisations and small start-ups, while others are working in health care or pursuing their interests in universities.

The lecturers on this programme are international experts in health data science and students will learn about cutting-edge research projects. The collaboration is part of the Farr Institute, a network of centres of excellence created to enhance the UK’s strength in data-intensive research. This MSc will draw on that collaboration, giving students access to the most advanced research in the field.

We work closely with a range of employing organisations to ensure that our graduates have the best possible preparation for a career in data science. This includes offering industry-sponsored dissertations for selected students.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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The Computer Science MSc provides a balance between computer science theory and practical software engineering skills, including teamwork for industrial or research clients. Read more

The Computer Science MSc provides a balance between computer science theory and practical software engineering skills, including teamwork for industrial or research clients. Graduates find employment in the IT industry, or complement their first degree subject with computer science knowledge, leading to interdisciplinary industrial positions and PhD research.

About this degree

You will learn fundamental aspects of how computers work by taking modules in computer architecture, operating systems, compilers, data structures and algorithms. You will also gain practical knowledge in areas such as human-computer interaction, App design, databases and software engineering. You will develop programming skills in modern languages, such as object-oriented Java for Android development. 

Team working, project planning and communication skills are developed by working in small groups developing software for real industrial and research clients. Optional modules allow specialisation in subjects such as functional programming, computer music, entrepreneurship and artificial intelligence.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits) and a research project (60 credits).

Core modules

  • Algorithmics (15 credits)
  • Architecture and Hardware (15 credits)
  • Design (15 credits)
  • Programming (15 credits)
  • Systems Infrastructure (15 credits)

Optional modules

Students must choose a minimum of 15 and a maximum of 45 credits from Group One options. For the remaining credits, students can choose up to 30 credits from Group Two options and up to 15 credits from Electives.

Group One Options (15 to 45 credits)

  • Database Systems (15 credits)
  • Entrepreneurship: Theory and Practice (15 credits)
  • Functional Programming (15 credits)
  • Interaction Design (15 credits)
  • Software Engineering (15 credits)

Group Two Options (up to 30 credits)

  • Affective Interaction (15 credits)
  • Artificial Intelligence and Neural Computing (15 credits)
  • Project Management (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

All students undertake an independent computer-based science project which culminates in a dissertation in the form of a project report.

Teaching and learning

The programme is delivered through a combination of lectures and tutorials. Lectures are often supported by laboratory work with help from demonstrators. Student performance is assessed by unseen written examinations, coursework and a substantial individual project.

Further information on modules and degree structure is available on the department website: Computer Science MSc

Careers

Graduates from UCL are keenly sought after by the world's leading organisations, and many progress in their careers to secure senior and influential positions. UCL Computer Science graduates are particularly valued as a result of the department's strong international reputation, strong links with industry, and ideal location close to the City of London. Our graduates secure careers in a wide variety of organisations; for example with global IT consultancies, as IT analysts with City banks, or as IT specialists within manufacturing industries.

Recent career destinations for this degree

  • Analyst and IT Consultant, KPMG
  • Associate Quantity Developer, Moody's
  • Clinical Systems Manager, Whittington Hospital (NHS)
  • Cyber Security Analyst / Developer, BAE Systems
  • PhD in System Engineering, City University of Hong Kong

Employability

This degree opens up many different career paths. Recent graduates have been employed by some of the world's leading IT companies such as Accenture, Barclays Capital and Credit Suisse. The entrepreneurial spirit is ignited in other students and they may either start their own companies or join dynamic start-ups. Other graduates have gone on to PhD study to conduct cutting-edge research in areas that interest them.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research.

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries from entertainment to finance.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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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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