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Masters Degrees (Mathematical Science)

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Master of Science in Mathematical Science. Students take modules in Mathematical Physics and Mathematics. At least 4 of the modules (at least 45 ECTS) must be taken at the Masters level (level 6 in Mathematical Physics and level 5 in Mathematics). Read more

Overview

Master of Science in Mathematical Science

Students take modules in Mathematical Physics and Mathematics. At least 4 of the modules (at least 45 ECTS) must be taken at the Masters level (level 6 in Mathematical Physics and level 5 in Mathematics). The remaining credits may be made up at levels 4, 5 or 6.


Minimum English language requirements:
- IELTS: 6.5 minimum overall score
- TOEFL (Paper based test): 585
- TOEFL (Internet based test): 95
- PTE (Pearson): 62

Maynooth University’s TOEFL code is 8850.

Course Structure

All module choices are subject to the approval of the Head of Department. Level 6 choices for Mathematical Physics are listed below. For other choices see the Mathematics Department modules at level 5 (see MSc in Mathematics MHR52) and Mathematical Physics Department modules at level 4. One of the Masters level modules may be replaced by a minor thesis subject to the approval of the Head of Department. Total credits 60.

Career Options

The course provides a solid foundation in Theoretical Physics/Applied Mathematics/Pure Mathematics for students who wish to pursue careers in science, engineering, commerce and technology. Graduates gain employment in a wide range of occupations including research, teaching, actuary, banking, software development, computational physics and computer modelling/simulation. Students who perform well may go on to the PhD programme.

Find out how to apply here https://www.maynoothuniversity.ie/mathematical-physics/our-courses/msc-mathematical-science#tabs-apply

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Master of Science in Mathematical Science. Students take modules in Mathematical Physics and Mathematics. At least 4 of the modules (at least 45 ECTS) must be taken at the Masters level (level 6 in Mathematical Physics and level 5 in Mathematics). Read more

Overview

Master of Science in Mathematical Science

Students take modules in Mathematical Physics and Mathematics. At least 4 of the modules (at least 45 ECTS) must be taken at the Masters level (level 6 in Mathematical Physics and level 5 in Mathematics). The remaining credits may be made up at levels 4, 5 or 6.

See the website https://www.maynoothuniversity.ie/mathematical-physics/our-courses/msc-mathematical-science-pt

Minimum English language requirements:
- IELTS: 6.5 minimum overall score
- TOEFL (Paper based test): 585
- TOEFL (Internet based test): 95
- PTE (Pearson): 62

National University of Ireland Maynooth’s TOEFL code is 8850.

Course Structure

All module choices are subject to the approval of the Head of Department. Level 6 choices for Mathematical Physics are listed below. For other choices see the Mathematics Department modules at level 5 (see MSc in Mathematics MHR52) and Mathematical Physics Department modules at level 4. One of the Masters level modules may be replaced by a minor thesis subject to the approval of the Head of Department. Total credits 60.

Career Options

The course provides a solid foundation in Theoretical Physics/Applied Mathematics/Pure Mathematics for students who wish to pursue careers in science, engineering, commerce and technology. Graduates gain employment in a wide range of occupations including research, teaching, actuary, banking, software development, computational physics and computer modelling/simulation. Students who perform well may go on to the PhD programme.

Find out how to apply here https://www.maynoothuniversity.ie/mathematical-physics/our-courses/msc-mathematical-science-pt#tabs-apply

Find information on Scholarships here https://www.maynoothuniversity.ie/study-maynooth/postgraduate-studies/fees-funding-scholarships

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This is a one year full-time or two or more years part-time taught course. Minimum English language requirements. - IELTS. 6.5 minimum overall score. Read more

Overview

This is a one year full-time or two or more years part-time taught course.


Minimum English language requirements:
- IELTS: 6.5 minimum overall score
- TOEFL (Paper based test): 585
- TOEFL (Internet based test): 95
- PTE (Pearson): 62

Maynooth University’s TOEFL code is 8850

Course Structure

Students take 60 credits of Mathematical Physics from the level 4 and level 3 modules.

Career Options

The course provides a solid foundation in Theoretical Physics/Applied Mathematics for students who wish to pursue careers in science, engineering, commerce and technology. Graduates gain employment in a wide range of occupations including research, teaching, actuary, banking, software development, computational physics and computer modelling/simulation.

Find out how to apply here https://www.maynoothuniversity.ie/mathematical-physics/our-courses/higher-diploma-mathematical-science-0#tabs-apply

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This is a one year full-time or two or more years part-time taught course. Minimum English language requirements. - IELTS. 6.5 minimum overall score. Read more

Overview

This is a one year full-time or two or more years part-time taught course.


Minimum English language requirements:
- IELTS: 6.5 minimum overall score
- TOEFL (Paper based test): 585
- TOEFL (Internet based test): 95
- PTE (Pearson): 62

Maynooth University’s TOEFL code is 8850

Course Structure

Students take 60 credits of Mathematical Physics from the level 4 and level 3 modules.

Career Options

The course provides a solid foundation in Theoretical Physics/Applied Mathematics for students who wish to pursue careers in science, engineering, commerce and technology. Graduates gain employment in a wide range of occupations including research, teaching, actuary, banking, software development, computational physics and computer modelling/simulation.

Find out how to apply here https://www.maynoothuniversity.ie/mathematical-physics/our-courses/higher-diploma-mathematical-science#tabs-apply

Find information on Scholarships here https://www.maynoothuniversity.ie/study-maynooth/postgraduate-studies/fees-funding-scholarships

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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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In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. Read more
In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.
The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, Complexity Theory, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.
Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

See the website http://www.ru.nl/masters/mathematics/foundations

Admission requirements for international students

1. A completed Bachelor's degree in Mathematics or Computer Science
In order to get admission to this Master’s you will need a completed Bachelor's in mathematics or computer science that have a strong mathematical background and theoretical interests. We will select students based on their motivation and their background. Mathematical maturity is essential and basic knowledge of logic and discrete mathematics is expected.

2. A proficiency in English
In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:
- TOEFL score of ≥575 (paper based) or ≥90 (internet based)
- IELTS score of ≥6.5
- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

There is a serious shortage of well-trained information specialists. Often students are offered a job before they have actually finished their study. About 20% of our graduates choose to go on to do a PhD but most find jobs as systems builders, ICT specialists or ICT managers in the private sector or within government.

Our approach to this field

In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.

The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, General Topology, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.

Our research in this field

Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

See the website http://www.ru.nl/masters/mathematics/foundations

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What do Facebook, the financial system, Internet or the brain have in common?. "Everything is connected, all is network". Read more
What do Facebook, the financial system, Internet or the brain have in common?

"Everything is connected, all is network"
From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals.

Our MSc Network Science will provide a thorough grounding in the core principles of modelling and analysis of complex and networked systems, along with the principal analytical and numerical methodologies. This will open to students a host of career opportunities in systems and networks modelling industries, spanning the IT, financial, and biomedical sectors, that are now requiring such specialist knowledge and skills.

Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), finance (financial risk and systemic instability, financial networks, interbank cross-correlations), marketing and IT (social media, data analytics), public health (epidemic spreading models), or biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), to cite a few. This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students with a mathematical background who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.

Why study your MSc Network Science at Queen Mary?
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.

We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. The coalescence of both groups expertises has fostered the creation of this unique MSc.

More about our two schools

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research, teaching excellence and unrivalled links with business and the public sector. The School of Mathematical Sciences has a distinguished history on itself. We have been conducting pioneering mathematical research since the 1950s, and as one of the largest mathematical departments in the UK, with over 50 members of staff, the school can offer diverse postgraduate study opportunities across the field, from pure and applied mathematics, to finance and statistics. Along with the MSc in Network Science, our cohort of postgraduate students specialise in Mathematics and Statistics, Mathematical Finance and Financial Computing. We are one of the UK’s leading universities in the most recent national assessment of research quality, we were placed ninth in the UK (REF 2014) amongst multi-faculty universities. This means that the teaching on our postgraduate programmes is directly inspired by the world-leading research of our academics. Our staff includes international leaders in many areas of mathematical research, and the School is a hive of activity, providing a vibrant intellectual space for postgraduate study.

The School of Electronic Engineering and Computer Science is internationally recognised for their pioneering and ground-breaking research in several areas including machine learning and applied network analysis. This expertise uniquely complements the more theoretical knowledge offered by the School of Mathematical Sciences, providing a well balanced mix of theory and applications and offering a deep and robust programme that combines the foundations of the mathematics of networks with the latest cutting edge applications in real world problems.

Additionally, Queen Mary holds a university-level Bronze Award for the Athena SWAN Charter, which recognises and celebrates good employment practice for women working in mathematics, science, engineering and technology in higher education and research.

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Computer science has a brilliant future! You could help to create new network solutions, build the future digital society, develop secure digital services, or be involved in a ground-breaking international software project. Read more
Computer science has a brilliant future! You could help to create new network solutions, build the future digital society, develop secure digital services, or be involved in a ground-breaking international software project. Perhaps you will develop algorithms for utilising genome data in medicine or optimise bus routes using positioning data. Do you wonder about all the things that can be automated? Or would you like to dig deeper and become a researcher?

In the Master’s programme in computer science you can become an expert in a wide range of fields. You will have access to the focus areas of research in computer science at the University of Helsinki: algorithms, distributed or networked systems, and software engineering. You will gain lasting professional skills for specialist, design, or managerial posts in the corporate world, or for research and doctoral education, since the Master’s programme in computer science gives you the aptitude for both independent working and multidisciplinary teamwork.

This education will give you:
-The ability to advance your knowledge in the different areas of computer science.
-The skill to seek, assess, and analyse scientific information in your own area of expertise, and apply the methods of the field in an ethical and sustainable way.
-The ability to act as expert in the field, and to develop the practices and methods of your field in cooperation with specialists from other fields.
-Oral and written communication skills in an international work environment.

The quality teaching within the computer science programme at the University of Helsinki has been highlighted repeatedly in national and international teaching assessments. The student-centred, in-depth learning gives you a solid basis for life-long learning. Studying at the leading research unit for computer science in Finland offers you constant interaction with current research and insight into the development patterns in the field.

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

In future, we will increasingly be using intelligent tools, consisting of networked hardware, software, services, and data. They will work based on intelligent, learning algorithms, data streams carried by communication protocols, and global infrastructures.

Within the Algorithms sub-programme, you will study effective algorithms and their application within other disciplines and in corporate life. Future IT systems will contain more and more intelligent components, the function of which will be based on complex mathematical models created automatically with the aid of machine-learning methods. The problems to be solved are computationally challenging, and the ever increasing amounts of data will create their own challenges when it comes to the efficiency of the algorithms needed.

The Networking and services sub-programme educates you to become an expert and strategic leader in the design and management of new global infrastructures. The infrastructures include Internet technologies in fixed networks and mobile environments, as well as the information and service networks built on top of them. Focus areas include the theory, data security, and trust within distributed systems, interactive systems, and the adaptability of services in a changing environment.

The Software systems sub-programme introduces you to the design and implementation of advanced software. The development of a shared software framework or platform for several software products is very demanding both technically and from the development project viewpoint. Developing such software requires technical skills, but also team- and project work, quality assurance, and communication. Within this sub-programme, you can specialise in software engineering, software technology, or information management, and study the current research questions in these areas in depth.

Selection of the Major

The sub-programmes in the Master’s programme for computer science are:
-Algorithms
-Networking and services
-Software systems

You can select any of these programmes according to your preferences at the beginning of your studies. The sub-programme determines which courses you should take.

Programme Structure

The Master’s programme comprises 120 credits, which can be completed in two years, in accordance with an approved personal study plan. The degree includes:
-80 credits of advanced courses, including shared courses within the programme, courses within the programme which support the thesis topic, the Master’s thesis (Pro gradu), 30 credits.
-40 credits of other courses from your own or other programmes. The other courses can include a work-orientation period.

Career Prospects

The employment outlook within the field is excellent. Masters of computer science find varied positions within the ICT field, both as employees and entrepreneurs. The nature of the education is also geared towards giving you an aptitude for managerial posts. All the sub-programmes provide the qualifications to find employment in a wide variety of jobs.

Software-system graduates often start their careers as software developers and designers, while network graduates often start with software at the infrastructure level (such as data communications, computation, or data entry). The skills learned in the algorithms sub-programme enable you to work on challenging tasks in various fields.

As a graduate you can find employment within small or large corporations as well as organisations in the private, public, or third sector. Due to the global nature of the field, you can find employment anywhere in the world. Taking modules from other education programmes will help you apply your computer science skills in other areas. Many jobs are based on these combinations.

Thanks to its strong scientific basis, the degree is also an excellent springboard to a doctoral programme.

Internationalization

There is a very international atmosphere within the programme, as nearly a third of the students come from abroad, and the advanced courses are instructed by international researchers.

In addition, the University of Helsinki and the Faculty of Science offer you many opportunities for international activities:
-Instruction in English within other education programmes.
-International tasks within the students’ organisations or union.
-Language courses at the Language Centre of the University of Helsinki.

You can also get information and counselling about independent international experience, such as:
-Student exchange in one of the exchange locations of the faculty or university.
-Traineeships abroad.

Computer science at the University of Helsinki is a popular exchange location, especially from Germany. Some 5-10 students come annually; exchange students have come from 14 countries in recent years. The students in the department have taken exchange periods in 16 countries in the past few years.

Research Focus

There are several multidisciplinary research projects under way at the Faculty of Science, which are being carried out in cooperation with the research institutes on the science campus and with other faculties, universities, and corporations. The role of computer science within these projects is to develop the basic methods of the discipline in strategic areas and to collaborate in depth with other disciplines.

The sub-programmes within the Master’s programme cover a considerable part of the strategic focus areas of computer science research at the University of Helsinki: algorithms, data analysis and machine learning, networking and services, software systems, bioinformatics, and data science.

Computer science is part of three Finnish Academy centres of excellence: for computational inference, inversion problems, and cancer genetics. These units represent the collaboration between computer science and other disciplines.

Computer science has coordinated the long-lived Algodan centre of excellence, which has been the basis for many current research groups.

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The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. Read more

Mission and goals

The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. It harmonises a solid scientific background with a command of advanced methodologies and technologies. The programme is characterised by a continuous synergy between Applied Mathematics and Engineering disciplines- The students may choose among three specialisations:
- Computational Science and Engineering
- Applied Statistics
- Quantitative Finance

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Career opportunities

The professional opportunities offered by this course are rather ample and varied: engineering consultancy companies that deal with complex computational problems; manufacturing or civil engineering companies where analyses based on the use of advanced mathematical tools are needed; banks, insurance companies and financial institutions making use of quantitative finance for risk analysis or forecast; companies that require statistical interpretation and the processing of complex data, or the simulation of different scenarios; public and private research institutes and laboratories.

Eligible students

Students holding a Bachelor degree in Mathematical Engineering, or in a related area with a solid background in the core disciplines of the programme, i.e. Applied Mathematics, Computer Science, Applied Physics or other Engineering disciplines are eligible for application. In particular, eligible students' past studies must include courses in different areas of Engineering (among Informatics, Economics & Business Organization, Electrotechnics, Automation, Electronics, Applied Physics, Civil Engineering) for at least 25% of the overall courses, as well as courses in different areas of Mathematics (Mathematical Analysis, Linear Algebra, Geometry, Probability, Statistics, Numerical Analysis, Optimization) for at least 33% of the overall courses.
The following tracks are available:
1. Computational Science and Engineering
2. Applied Statistics
3. Quantitative Finance

Eligible students must clearly specify the track they are applying for in their motivation letter.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mathematical_Engineering.pdf
The Master of Science in Mathematical Engineering (MSME) aims to form an innovative and flexible professional profile, endowed with a wide spectrum of basic scientific notions and engineering principles, together with a deep knowledge of modern pure and applied mathematical techniques. MSME is characterized by a continuous synergy between Mathematics and Engineering methods, oriented to the modelling, analysis and solution of complex planning, control and management problems, and provides the students with the possibility to face problems from various scientific, financial and/or technological areas. The MSME graduates can find employment in Engineering companies specialized in handling complex computational problems, requiring a multidisciplinary knowledge; in companies manufacturing industrial goods for which design analysis based on the use of advanced mathematical procedures are required; in service societies, banks, insurance companies, finance or consultant agencies for the statistical interpretation and the simulation of complex situations related to the analysis of large number of data (e.g. management and optimization of services, data mining, information retrieval) or for handling financial products and risk management; in public and private institutions. The programme is taught in English.

Subjects

Three main tracks available:
1. Computational Science for Engineering
Real and functional analysis; algorithms and parallel programming; numerical and theoretical analysis for partial differential equations; fluid mechanics; computational fluid dynamics advanced programming techniques for scientific computing;

2. Statistics
Real and functional analysis; algorithms and parallel programming; stochastic dynamical models; applied statistics, model identification and data analysis; Bayesian statistics

3. Mathematical Finance
Real and functional analysis; algorithms and parallel programming; stochastic differential equations; mathematical finance; financial engineering; model identification and data analysis.

In the motivation letter the student must clearly specify the track he/she is applying for.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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Environmental earth science (or geoscience) covers a range of topics including hydrology, sedimentology and geomorphology. This course provides specialist skills and knowledge for science graduates wanting to pursue careers in environmental earth science. Read more

What is environmental earth science?

Environmental earth science (or geoscience) covers a range of topics including hydrology, sedimentology and geomorphology.

Who is this course for?

This course provides specialist skills and knowledge for science graduates wanting to pursue careers in environmental earth science. Environmental scientists undertake work such as developing ways to minimise the impacts of humans on the natural environment.

Course learning outcomes

The graduates of James Cook University are prepared and equipped to create a brighter future for life in the tropics world-wide.
JCU graduates are committed to lifelong learning, intellectual development, and to the display of exemplary personal, professional and ethical standards. They have a sense of their place in the tropics and are charged with professional, community, and environmental responsibility. JCU graduates appreciate the need to embrace and be acquainted with the Aboriginal and Torres Strait Islander Peoples of Australia. They are committed to reconciliation, diversity and sustainability. They exhibit a willingness to lead and to contribute to the intellectual, environmental, cultural, economic and social challenges of regional, national, and international communities of the tropics.
On successful completion of the Graduate Diploma of Science, graduates will be able to:
*Integrate and apply advanced theoretical and technical knowledge in one or more science disciplines
*Retrieve, analyse, synthesise and evaluate knowledge from a range of sources
*Plan and conduct reliable, evidence-based laboratory and/or field experiments/practices by selecting and applying methods, techniques and tools, as appropriate to one or more science disciplines
*Organise, analyse and interpret complex scientific data using mathematical, statistical and technological skills
*Communicate complex scientific ideas, arguments and conclusions clearly and coherently to a variety of audiences through advanced written and oral English language skills and a variety of media
*Identify, analyse and generate solutions to unpredictable or complex problems, especially related to tropical, rural, remote or Indigenous contexts, by applying scientific knowledge and skills with initiative and high level judgement
*Explain and apply regulatory requirements, ethical principles and, where appropriate, cultural frameworks, to work effectively, responsibly and safely in diverse contexts
*Reflect on current skills, knowledge and attitudes to manage their professional learning needs and performance, autonomously and in collaboration with others.

Award title

GRADUATE DIPLOMA OF SCIENCE (GDipSc)

Course articulation

Students who complete the Graduate Diploma of Science are eligible for entry to the Master of Science, and may be granted advanced standing for all subjects completed under the Graduate Diploma.

Entry requirements (Additional)

English band level 1 - the minimum English Language test scores you need are:
*Academic IELTS – 6.0 (no component lower than 5.5), OR
*TOEFL – 550 (plus minimum Test of Written English score of 4.0), OR
*TOEFL (internet based) – 79 (minimum writing score of 19), OR
*Pearson (PTE Academic) - 57

If you meet the academic requirements for a course, but not the minimum English requirements, you will be given the opportunity to take an English program to improve your skills in addition to an offer to study a degree at JCU. The JCU degree offer will be conditional upon the student gaining a certain grade in their English program. This combination of courses is called a packaged offer.
JCU’s English language provider is Union Institute of Languages (UIL). UIL have teaching centres on both the Townsville and Cairns campuses.

Minimum English language proficiency requirements

Applicants of non-English speaking backgrounds must meet the English language proficiency requirements of Band 1 – Schedule II of the JCU Admissions Policy.

Why JCU?

James Cook University brings together a team of academic and associate staff across multiple disciplines.
*Nationally-recognised leader in geoscience
*state-of-the-art research and teaching facilities
*internationally-acclaimed academic teaching staff
*strong collaboration with industry and research organisations, both locally and internationally.

Career Opportunities

A postgraduate qualification from JCU can enhance your career prospects, enable you to reskill and change careers completely, or develop a specialist area of expertise and personal interest.
Earth science and environmental science graduates enjoy well-paid careers in Australia and overseas. A range of opportunities await graduates in the academia as well as in private and public sectors.
As an Environ mental Scientist, for instance, you will measure and record features of the environment and study, assess and develop methods of controlling or minimizing the harmful effects of hum an activity on the environment.
Graduates can also get jobs as research assistants or support staff for teaching. With a PhD, you can gain research positions (Postdoctoral, Fellowships) that are often funded for a few years or apply for permanent positions as a lecturer and researcher.

Application deadlines

*1st February for commencement in semester one (February)
*1st July for commencement in semester two (mid-year/July)

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The primary aim of this course is to educate you to MSc level in the theoretical and practical aspects of mathematical problem solving, mathematical model development, creating software solutions and communication of results. Read more
The primary aim of this course is to educate you to MSc level in the theoretical and practical aspects of mathematical problem solving, mathematical model development, creating software solutions and communication of results.

This course provides training in the use and development of reliable numerical methods and corresponding software. It aims to train graduates with a mathematical background to develop and apply their skills to the solution of real problems. It covers the underlying mathematical ideas and techniques and the use and design of mathematical software. Several application areas are examined in detail. It develops skills in mathematical problem-solving, scientific computing, and technical communication.

Training is also provided in general computing skills, mathematical typsetting, mathematical writing, desktop and web-based mathematical software development, and the use of computer languages and packages including Mathematica, parallel computing, C#, 3D graphics and animation, and visualisation.

The MSC is now available fully online and can be taken over 12 months full time or 24 months part time.

Visit the website: http://www.ucc.ie/en/ckr36/

Course Details

By the end of the course, you will be able to:

- use the description of a real world problem to develop a reasonable mathematical model in consultation with the scientific literature and possibly experts in the area
- carry out appropriate mathematical analysis
- select or develop an appropriate numerical method and write a computer programme which gives access to a sensible solution to the problem
- present and interpret these results for a potential client or a non-technical audience

Modules

Module descriptions - http://www.ucc.ie/calendar/postgraduate/Masters/science/page05.html#mathematical

AM6001 Introduction to Mathematica (5 credits)
AM6002 Numerical Analysis with Mathematica (5 credits)
AM6003 Cellular Automata (5 credits)
AM6004 Applied Nonlinear Analysis (Computational Aspects) (5 credits)
AM6005 Modelling of Systems with Strong Nonlinearities (5 credits)
AM6006 Mathematical Modelling of Biological Systems with Differential Equations (5 credits)
AM6007 Object Oriented Programming with Numerical Examples (10 credits)
AM6008 Developing Windowed Applications and Web-based Development for Scientific Applications (5 credits)
AM6009 3D Computer Graphics and Animation for Scientific Visualisation (5 credits)
AM6010 Topics in Applied Mathematical Modelling (5 credits)
AM6011 Advanced Mathematical Models and Parallel Computing with Mathematica (5 credits)
AM6012 Minor Dissertation (30 credits)

Format

The course places great emphasis on hands-on practical skills. There is a computer laboratory allocated solely for the use of MSc students. PCs are preloaded with all the required software and tools. Online students are expected to have a suitable PC or laptop available; all required software is provided for installation to faciliate course work. Online teaching hours, involving lecturers, tutorials and practical demonstrations, usually take place in the morninbg. The rest of the time, you are expected to do exercises, assignments and generally put in the time required to acquire key skills.

Assessment

Continuous assessment is the primary method of examining. In each module, typically 40% of the marks are available for take-home assignments and the remaining 60% of marks are examined by a practical computer-based examination. Final projects are read and examined by at least two members of staff.

For more information, please see the Book of Modules 2015/2016 - http://www.ucc.ie/calendar/postgraduate/Masters/science/page05.html#mathematical

Careers

Quantitative graduates with software skills are in high demand in industry according to the Governments Expert Group on Future Skills Needs. Demand for these skills is project to rise over the coming years not just in Ireland but in the EU and globally. Graduates have recently secured jobs in the following areas: banking, financial trading, consultancy, online gambling firms, software development, logistics, data analysis and with companies such as AIB, McAfee, Fexco, DeCare Systems, MpStor, the Tyndall Institute, Matchbook.com, First Derivatives and KPMG.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights. Read more
Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights.

Who is it for?

This programme is for students who have a numerate first degree or can demonstrate numerate skills. Students are often at the early stages of their careers in diverse professions including economics, statistics and computer science.

Students will have a curiosity about data, and will want to learn new techniques to boost their career and be part of exciting current industry developments. The MSc in Data Science includes some complex programming tasks because of the applied nature of the course, so many students have a mathematics or statistics background and enjoy working with algorithms.

Objectives

The demand for data scientists in the UK has grown more than ten-fold in the past five years *. The amount of data in the world is growing exponentially. From analysing tyre performance to detecting problem gamblers, wherever data exists, there are opportunities to apply it.

City’s MSc Data Science programme covers the intersection of computer science and statistics, machine learning and practical applications. We explore areas such as visualisation because we believe that data science is about generating insight into data as well as its communication in practice.

The programme focuses on machine learning as the most exciting technology for data and we have learned from our own graduates that this is of high value when it comes to employment within the field. At City, we have excellent expertise in machine learning and the facilities students need to learn the technical aspects of data analysis. We also have a world-leading centre for data visualisation, where students get exposed to the latest developments on presenting and communicating their results – a highly sought after skill.

Placements

There is the opportunity to do an internship as part of the programme. The final project, which is normally three months for a full-time student, can be extended to six months if you want to study within a specific organisation. When it comes to the big data and data science area, we have established relationships with organisations including the BBC, Microsoft and The British Library so you can be confident that with City, your access to professional experience is unparalleled. One recent student undertook an internship with Google and has since secured a job within the company.

Academic facilities

The School's computer science laboratories are equipped with the latest up-to-date hardware and software. From Oracle’s leading commercial object-relational database server to PCs with state-of-the-art NVidia GPUs for computer graphics, you will have access to an array of tools to support your learning.

The MSc Data Science programme offers two (three by mid 2016) dedicated computer servers for the Big Data module, which you can also use for your final project to analyse large data sets. We give you the opportunity to undertake training in MATLAB, the most popular numerical and technical programming environment, while you study.

Scholarships

A scholarship for the full fees of the MSc will be offered to an outstanding applicant. The scholarship is available to UK/EU and overseas students, studying full-time. To be considered for the scholarship, please include with your full application a one-page essay with your answer to the question:

'What are the challenges that Data Science faces and how would you address those challenges?'

The submission deadline for anyone wishing to be considered for the scholarship is: 1 MAY 2017

Teaching and learning

The teaching and learning methods we use mean that students’ specialist knowledge and autonomy increase as they progress through each module. Active researchers guide your progress in the areas of machine learning, data visualization, and high-performance computing, which culminates with an individual project. This is an original piece of research conducted with academic supervision, but largely independently and, where appropriate, in collaboration with industrial partners.

Taught modules are delivered through a series of 20 hours of lectures and 10 hours of tutorials/laboratory sessions. Lectures are normally used to:
-Present and exemplify the concepts underpinning a particular subject.
-Highlight the most significant aspects of the syllabus.
-Indicate additional topics and resources for private study.

Tutorials help you develop the skills to apply the concepts we have covered in the lectures. We normally achieve this through practical problem solving contexts.

Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools.

In addition to lectures, laboratory sessions and tutorial support, you also have access to a personal tutor. This is an academic member of staff from whom you can gain learning support throughout your degree. In addition, City’s online learning environment Moodle contains resources for each of the modules from lecture notes and lab materials, to coursework feedback, model answers, and an interactive discussion forum.

We expect you to study independently and complete coursework for each module. This should amount to approximately 120 hours per module if you are studying full time. Each module is assessed through a combination of written examination and coursework, where you will need to answer theoretical and practical questions to demonstrate that you can analyse and apply data science methods and techniques.

The individual project is a substantial task. It is your opportunity to develop a research-related topic under the supervision of an academic member of staff. This is the moment when you can apply what you have learnt to solve a real-world problem using large datasets from industry, academia or government and use your knowledge of collecting and processing real data, designing and implementing big data methods and applying and evaluating data analysis, visualisation and prediction techniques. At the end of the project you submit a substantial MSc project report, which becomes the mode of assessment for this part of the programme.

Course content

Data science is the area of study concerned with the extraction of insight from large collections of data.

The course covers the study, integration and application of advanced methods and techniques from:
-Data analysis and machine learning
-Data visualisation and visual analytics
-High-performance, parallel and distributed computing
-Knowledge representation and reasoning
-Neural computation
-Signal processing
-Data management and information retrieval.

It gives you the opportunity to specialise so, once you graduate, you can apply data science to any sector from health to retail. By engaging with researchers and industrial partners during the programme, you can develop your knowledge and skills within a real-world context in each of the above areas.

Core modules
-Principles of data science (15 credits)
-Machine learning (15 credits)
-Big Data (15 credits)
-Neural computing (15 credits)
-Visual analytics (15 credits)
-Research methods and professional issues (15 credits)

Elective modules
-Advanced programming: concurrency (15 credits)
-Readings in computer science (15 credits)
-Advanced databases (15 credits)
-Information retrieval (15 credits)
-Data visualisation (15 credits)
-Digital signal processing and audio programming (15 credits)
-Cloud computing (15 credits)
-Computer vision (15 credits)
-Software agents (15 credits)

Individual project - (60 credits)

Career prospects

From health to retail, and from the IT industry to government, the Data Science MSc will prepare you for a successful career as a data scientist. You will graduate with specialist skills in data acquisition, information extraction, aggregation and representation, data analysis, knowledge extraction and explanation, which are in high demand.

City's unique internships, our emphasis on machine learning and visual analytics, together with our links with the industry and Tech City, should help you gain employment as a specialist in data analysis and visualization. Graduates starting a new business can benefit from City's London City Incubator and City's links with Tech City, providing support for start-up businesses.

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The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Read more
The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Data science is a growing and important field of study with a fast-growing number of jobs and opportunities within the private and public sector. The application of theory and methods to real-world problems and applications is at the core of data science, which aims especially to use and to exploit big data.

If you are interested in solving real-world problems, you like to develop skills to use smart devices efficiently, you want to use and to foster your understanding of mathematics, and you are interested and keen to use statistical techniques and methods to interpret data, MSc Data Science at Essex is for you. You study a balance of solid theory and practical application including:
-Computer science
-Programming
-Statistics
-Data analysis
-Probability

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

You also benefit from being taught in our School of Computer Science and Electronic Engineering, who are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of their research rated ‘world-leading’ or ‘internationally excellent’ (REF 2014).

The collaborative work between our departments has resulted in well-known research in areas including artificial intelligence, data analysis, data analytics, data mining, data science, machine learning and operations research.

Our expert staff

Our Department of Mathematical Sciences is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

The academic staff in our School of Computer Science and Electronic Engineering are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist staff working on data analytics include Dr Paul Scott, who researches data mining, models of memory and attention, and artificial intelligence, and Professor Maria Fasli, who researches data exploration, analysis and modelling of complex, structured and unstructured data, big data, cognitive agents, and web search assistants.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We have six laboratories that are exclusively for computer science and electronic engineering students
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-You have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
-We host regular events and seminars throughout the year
-Collaborate with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
-The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to our internationally outstanding data science environment

Your future

With a predicted shortage of data scientists, now is the time to future-proof your career. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course opens the door to almost any industry, from health, to government, to publishing.

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Dissertation (optional)
-MSc Project and Dissertation (optional)
-Applied Statistics
-Machine Learning and Data Mining
-Modelling Experimental Data
-Text Analytics
-Artificial Neural Networks (optional)
-Bayesian Computational Statistics (optional)
-Big-Data for Computational Finance (optional)
-Combinatorial Optimisation (optional)
-High Performance Computing (optional)
-Natural Language Engineering (optional)
-Nonlinear Programming (optional)
-Professional Practice and Research Methodology (optional)
-Programming in Python (optional)
-Information Retrieval (optional)
-Data Science and Decision Making (optional)
-Research Methods (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)

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The MSc in Computer Science is for graduates from a different discipline interested in a career in computer science. Computing underpins much of our professional and personal lives. Read more
The MSc in Computer Science is for graduates from a different discipline interested in a career in computer science.

Why study computer science with us?

Computing underpins much of our professional and personal lives. There is a growing need for individuals trained in one discipline who are also skilled in computer science.

If you are a graduate with a non-computing first degree then our MSc will:

- provide you with a sound foundation in practical and theoretical aspects of computer science
- help you change career, with skills desirable to a huge number of industries
- enhance your employability with transferable skills
- prepare you for PhD study

No prior background in computer science is necessary.

What will I learn?

Semester one offers a broad overview of computer science through a series of core units.

Semester two focusses on advanced and emerging areas of computer science. You will have the opportunity to specialise in one or more areas of the discipline.

The final semester is for your dissertation. You will:

- demonstrate the knowledge, skills and reflective insights you have have gained
- apply them to the investigation and/or development of new software systems.

Visit the Department of Computer Science (http://www.bath.ac.uk/comp-sci/) for further information on the department.

Visit the website http://www.bath.ac.uk/science/graduate-school/taught-programmes/msc-computer-science/index.html

Programme structure

The programme covers three semesters.

In the first semester we immerse students in the practical and theoretical foundations of the discipline.

In the second semester we build upon these foundations allowing students to specialise in one or more areas of the discipline.

The third semester is dedicated to a dissertation. Students combine their acquired knowledge to produce a novel software element or conduct novel research and critique their achievements. Please visit our research pages for a an overview of our research (http://www.bath.ac.uk/comp-sci/research/).

Career opportunities

Opportunities are extensive and we expect our graduates to move into computing careers in the leading:
- computer companies
- IT consultancy firms
- banks
- companies
- agencies
- educational establishments

About the department

The new Department of Computer Science began life in August 2001, emerging from the Computing Group of the Department of Mathematical Sciences. It is a research-led department with a strong record in interdisciplinary research and postgraduate teaching.

MSc
Our Masters programmes are designed to give you a wide range of knowledge so that you can build a career in the fast-moving industry of computing. The programmes are taught by recognised experts in each field, offering you, the student, a cutting-edge experience and a qualification which is both academic and commercially relevant. You will be exposed to the latest science and technology in your chosen specialist area, to complement previously-gained knowledge and skills from your undergraduate degree.

MPhil/PhD
The Department supports a strategic range of computer science research at PhD level and beyond. Our main research interests include Human Computer Interaction, Visual Computing, Mathematical Foundations, and Intelligent Systems. Research is pursued both in fundamental theoretical development and a range of application areas.

EngD in Digital Media
The Engineering Doctorate (EngD) in Digital Media is an alternative to the traditional PhD for students who want a career in industry. A four-year programme combines PhD-level research projects with taught courses, and students spend about 75% of their time working directly with a company.

Facilities and equipment
LAN and WAN, state-of-the-art HCI laboratory, audio laboratory.

International and industrial links
The Department has active collaborations with academics in leading universities in Europe, Australasia, the USA and Japan. Strong links with industry, e.g. HP labs, Airbus, Qinetiq, Westland, Toshiba and Vodafone.

Careers information
High employment records for undergraduate and postgraduate students. Good links with employers

Find out more about the department here - http://www.bath.ac.uk/comp-sci/

Find out how to apply here - http://www.bath.ac.uk/science/graduate-school/taught-programmes/how-to-apply/

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A solid, theoretical understanding of computer technology with plenty of attention for the wide range of ICT applications. The enormous and rapidly growing power of ICT is the main driving force shaping our modern society. Read more
A solid, theoretical understanding of computer technology with plenty of attention for the wide range of ICT applications.

The enormous and rapidly growing power of ICT is the main driving force shaping our modern society. This goes beyond the technical and economical aspects. ICT is also essential in research as all sciences benefit from the raw power of software in processing huge quantities of data. But how do we manage and control the complexity of modern software? How can we make the most of the opportunities? And, not to be forgotten, how can we secure the ICT infrastructures we so heavily rely on? The Master’s programme in Computing Science covers all these aspects.

We offer specialisations in each terrain: security, software, data and the mathematics at the base of it all. These are not, however, isolated disciplines. We also look at the interesting interplay between them. For example, by taking privacy into account when dealing with big data. And by doing a thorough analysis of newly designed software to prevent security breaches later. Thanks to a large number of optional courses, you can decide where you want your focus to be.

The job opportunities in computer science are excellent: many of our students get offered jobs before they’ve even graduated and almost all have positions within six months after graduating. Many of our graduates find jobs as systems builders, ICT specialists or ICT managers and a few continue as researchers.

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

Specialisations

- Cyber Security
You’ll learn to assess the security of existing ICT solutions, and how to develop more secure solutions for the future. This specialisation is offered in collaboration with the Eindhoven University of Technology, meaning you get taught by many of the best cyber security experts in the country.

- Data Science
You’ll learn how to turn real-world data sets into tools and useful insights, with the help of software and algorithms. Radboud University and the iCIS research institute are leading in research on legal and privacy aspects of data science and on the societal and administrative impact of data science.

- Mathematical Foundations of Computer Science
You’ll come to understand the fundamental mathematical concepts of computation and information in order to stretch the boundaries of computer technology. We’re the only specialisation in the country – and one of the few in the world – to focus on the theoretical and abstract playing field linking mathematics and computer science.

- Software Science
You’ll learn how to design high-level software that guarantees safety while controlling its complexity. At Radboud University, we are specialised in model based development. In other words, writing and testing code before they are unleashed in the real world or built into an expensive prototype.

- Societal Master's specialisations
You can either follow one of the above-mentioned research Master's specialisations as a whole (2 years), or you can combine the first year of the research specialisation with an additional year of one of the societal Master’s specialisations, namely:
- Science in Society
- Science, Management and Innovation

Why study Computing Science at Radboud University?

- All of our specialisations are closely related to the research carried out within the Institute for Computing and Information Science (iCIS).
- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.
- There are plenty of high profile companies in the vicinity such as Philips and ASML, where you could do an internship or the research for your Master’s project.
- Exceptional students who choose the Data Science specialisation have the opportunity to do a double degree in Computing Science together with the specialisation in Web and Language Interaction (Artificial Intelligence). This will take three instead of two years.

Career prospects

There is a serious shortage of well-trained information specialists. Often students are offered a job before they have actually finished their study. About 20% of our graduates choose to go on to do a PhD but most find jobs as systems builders, ICT specialists or ICT managers in the private sector or within government.

Our research in this field

The Institute for Computing and Information Science (iCIS) is the research institute that is connected to Radboud University. Within this institute there are three research sections:
- Model Based System Development
- Digital Security
- Intelligent Systems

Within each research section there are different departments/groups that have their own research. On the websites of the research sections you will find more information about their research, publications, the departments/groups and contact information.

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

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