• Xi’an Jiaotong-Liverpool University Featured Masters Courses
  • Aberystwyth University Featured Masters Courses
  • Birmingham City University Featured Masters Courses
  • University of Derby Online Learning Featured Masters Courses
  • University of Surrey Featured Masters Courses
  • Northumbria University Featured Masters Courses
  • University of Bristol Featured Masters Courses
University of Nottingham in China Featured Masters Courses
FindA University Ltd Featured Masters Courses
Cass Business School Featured Masters Courses
Liverpool John Moores University Featured Masters Courses
University of the West of England, Bristol Featured Masters Courses
"parallel" AND "computing…×
0 miles

Masters Degrees (Parallel Computing)

We have 104 Masters Degrees (Parallel Computing)

  • "parallel" AND "computing" ×
  • clear all
Showing 1 to 15 of 104
Order by 
The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Read more
The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are well-equipped to proceed to doctoral research or directly into employment in industry, the professions, and the public service. It also provides training for the academic researchers and teachers of the future, encouraging the pursuit of research in computational methods for science and technology disciplines, thus being an important gateway for entering PhD programmes containing a substantial component of computational modelling.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/pcphmpscm

Course detail

The MPhil in Scientific Computing has a research and a taught element. The research element is a project on a science or technology topic which is studied by means of scientific computation. The taught element comprises of core lecture courses on topics of scientific computing and elective lecture courses relevant to the science or technology topic of the project. Most of the projects are expected to make use of the University’s High Performance Computing Service.

The students will attend lecture courses during Michaelmas Term (some courses may be during Lent Term) and then they will undertake a substantial Research Project over the next 6 months (from March to the end of August) in a participating Department. The research element aims to provide essential skills for continuation to a PhD programme or employment, as well as to assess and enhance the research capacity of the students. It is based on a science or technology topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners who are working with the participating Departments and may be sponsoring the research project.

There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively.

Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments on the core courses 25%; written examinations on the elective courses 25%.

Learning Outcomes

By the end of the course, students will have:

- a comprehensive understanding of numerical methods, and a thorough knowledge of the literature, applicable to their own research;
- demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
- shown abilities in the critical evaluation of current research and research techniques and methodologies;
- demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Format

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project.

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project. There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively. Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments 25%; written examinations 25%.

The core lectures are on topics of high performance scientific computing numerical analysis and advanced numerical methods and techniques. They are organized by the Centre for Scientific Computing and are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their dissertation and for their general education in scientific computing.

In particular, their objective is to introduce students to the simulation science pipeline of problem identification, modelling, simulation and evaluation - all from the perspective of employing high-performance computing. Numerical discretisation of mathematical models will be a priority, with a specific emphasis on understanding the trade-offs (in terms of modelling time, pre-processing time, computational time, and post-processing time) that must be made when solving realistic science and engineering problems. Understanding and working with computational methods and parallel computing will be a high priority. To help the students understand the material, the lecturers will furnish the courses with practical coursework assignments.

The lectures on topics of numerical analysis and HPC are complemented with hands-on practicals using Linux-based laptops provided by the course (students may bring their own), as well as on the University’s High Performance Computing Service.

Appropriate elective lecture courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor. While every effort is made within the Departments to arrange the timetable in a coherent fashion, it is inevitable that some combinations of courses will be ruled out by their schedule, particularly if the choices span more than one department.

Continuing

For continuation to a PhD programme in Scientific Computing, students are required to gain a Distinction (overall grade equal or greater than 75%).

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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

The MSc in High Performance and Scientific Computing is for you if you are a graduate in a scientific or engineering discipline and want to specialise in applications of High Performance computing in your chosen scientific area. During your studies in High Performance and Scientific Computing you will develop your computational and scientific knowledge and skills in tandem helping emphasise their inter-dependence.

On the course in High Performance and Scientific Computing you will develop a solid knowledge base of high performance computing tools and concepts with a flexibility in terms of techniques and applications. As s student of the MSc High Performance and Scientific Computing you will take core computational modules in addition to specialising in high performance computing applications in a scientific discipline that defines the route you have chosen (Biosciences, Computer Science, Geography or Physics). You will also be encouraged to take at least one module in a related discipline.

Modules of High Performance and Scientific Computing MSc

The modules you study on the High Performance and Scientific Computing MSc depend on the route you choose and routes are as follows:

Biosciences route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Conservation of Aquatic Resources or Environmental Impact Assessment

Ecosystems

Research Project in Environmental Biology

+ 10 credits from optional modules

Computer Science route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Software Engineering

Data Visualization

MSc Project

+ 30 credits from optional modules

Geography route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Modelling Earth Systems or Satellite Remote Sensing or Climate Change – Past, Present and Future or Geographical Information Systems

Research Project

+ 10 credits from optional modules

Physics route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Monte Carlo Methods

Quantum Information Processing

Phase Transitions and Critical Phenomena

Physics Project

+ 20 credits from optional modules

Optional Modules (High Performance and Scientific Computing MSc):

Software Engineering

Data Visualization

Monte Carlo Methods

Quantum Information Processing

Phase Transitions and Critical Phenomena

Modelling Earth Systems

Satellite Remote Sensing

Climate Change – Past, Present and Future

Geographical Information Systems

Conservation of Aquatic Resources

Environmental Impact Assessment

Ecosystems

Facilities

Students of the High Performance and Scientific Computing programme will benefit from the Department that is well-resourced to support research. Swansea physics graduates are more fortunate than most, gaining unique insights into exciting cutting-edge areas of physics due to the specialized research interests of all the teaching staff. This combined with a great staff-student ratio enables individual supervision in advanced final year research projects. Projects range from superconductivity and nano-technology to superstring theory and anti-matter. The success of this programme is apparent in the large proportion of our M.Phys. students who seek to continue with postgraduate programmes in research.

Specialist equipment includes:

a low-energy positron beam with a highfield superconducting magnet for the study of positronium

a number of CW and pulsed laser systems

scanning tunnelling electron and nearfield optical microscopes

a Raman microscope

a 72 CPU parallel cluster

access to the IBM-built ‘Blue C’ Supercomputer at Swansea University and is part of the shared use of the teraflop QCDOC facility based in Edinburgh

The Physics laboratories and teaching rooms were refurbished during 2012 and were officially opened by Professor Lyn Evans, Project Leader of the Large Hadron Collider at CERN. This major refurbishment was made possible through the University’s capital programme, the College of Science, and a generous bequest made to the Physics Department by Dr Gething Morgan Lewis FRSE, an eminent physicist who grew up in Ystalyfera in the Swansea Valley and was educated at Brecon College.



Read less
You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research. Read more

You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.

Our staff have a wealth of expertise across all areas of HPC, parallel programming technologies and data science.

This MSc programme has a strong practical focus and provide access to leading- edge HPC systems such as ARCHER, which is the UK’s largest, fastest and most powerful supercomputer, with more than 100,000 CPU cores.

HPC is the use of powerful processors, networks and parallel supercomputers to tackle problems that are very computationally or data-intensive. You will learn leading-edge HPC technologies and skills to exploit the full potential of the world’s largest supercomputers and multicore processors. This is a well-established programme that has been successful in training generations of specialists in parallel programming.

Programme structure

The MSc programme takes the form of two semesters of taught courses followed by a dissertation project.

Your studies will have a strong practical focus and you will have access to a wide range of HPC platforms and technologies. You will take seven compulsory courses, which provide a broad-based coverage of the fundamentals of HPC, parallel computing and data science. The option courses focus on specialist areas relevant to computational science. Assessment is by a combination of coursework and examination.

Taught courses

Compulsory courses:

  • HPC Architectures (Semester 1)
  • Message-Passing Programming (Semester 1)
  • Programming Skills (Semester 1)
  • Threaded Programming (Semester 1)
  • Software Development (Semester 2)
  • Project Preparation (Semester 2)
  • HPC Ecosystem (Semester 2)

Optional courses:

  • Fundamentals of Data Management (Semester 1)
  • Parallel Numerical Algorithms (Semester 1)
  • Parallel Programming Languages (Semester 1)
  • Advanced Parallel Programming (Semester 2)
  • Data Analytics with High Performance Computing (Semester 2)
  • Parallel Design Patterns (Semester 2)
  • Performance Programming (Semester 2)
  • Courses from the School of Informatics, Mathematics or Physics (up to 30 credits)

Dissertation

After completing the taught courses, students work on a three-month individual project leading to a dissertation.

Dissertation projects may be either research-based or industry-based with an external organisation, with opportunities for placements in local companies.

Industry-based dissertation projects

Through our strong links with industry, we offer our students the opportunity to undertake their dissertation project with one of a wide range of local companies.

An industry-based dissertation project can give you the opportunity to enhance your skills and employability by tackling a real-world project, gaining workplace experience, exploring potential career paths and building relationships with local companies.

Career opportunities

Our graduates are employed across a range of commercial areas, for example software development, petroleum engineering, finance and HPC support. Others have gone on to PhD research in fields that use HPC technologies, including astrophysics, biology, chemistry, geosciences, informatics and materials science.



Read less
In order to master the development process, you will obtain a firm foundation of design methods, software and hardware architectures, as well as programming of embedded systems. Read more

In order to master the development process, you will obtain a firm foundation of design methods, software and hardware architectures, as well as programming of embedded systems. Together with innovation and entrepreneurship studies, the Programme enables you to work in the embedded systems industry from start-ups to large-scale enterprises.

After graduation, you can pursue a career in academia, industry or the public sector.

Programme structure

1. Advanced-level studies in the major subject (65-70 ECTS)

  • Compulsory courses
  • Compulsory as well as optional courses

2. Optional and language studies (20-25 ECTS)

  • Optional studies in the minor subject (20 ECTS)
  • Language studies (0-5 ECTS)

3. Master’s thesis (30 ECTS)

Academic excellence and experience

Master’s Degree Programme in Embedded Computing is a two-year programme in the field of technology. It is designed to give you understanding of theoretical issues for starting PhD studies in the fields of embedded computing, cyber-physical systems (CPS) and internet of things (IoT). It also provides you with practical competences for challenging engineering jobs in the embedded systems industry.

The goal of the Programme is to offer education on modern embedded system design and modelling. Both hardware and software aspects are covered. You will obtain a firm foundation to design, model and implement embedded systems, including cyber-physical and IoT systems as well.

To master the development process, you will have an understanding of:

  • design constraints
  • hardware/software tradeoffs
  • design methods and software
  • hardware architectures
  • low-level programming of embedded and IoT systems

Research in the Programme focuses on Internet of Things (IoT), novel massively parallel computing platforms and paradigms, as well as autonomous embedded and cyber physical systems (CPS). The key application domains for the research are personal health, safety and well-being. The focus is on application development and implementation tools for multiprocessor platforms that are developed within the laboratory and wireless sensor networks.

Master's thesis and topics

In the Master’s thesis, you must prove your ability to do scientific work. You need to master management of research methods, knowledge of the research field and skill of scientific writing.

The goal of the Master’s thesis is:

  • to train independent problem solving for demanding research questions
  • to train presentation and argumentation skills, both oral and written
  • to train search and critical evaluation of information
  • to develop an ability to engage in a constructive dialogue with related disciplines
  • to gain insight into actual research and development work as well as the possibilities and constraints of embedded computing methods in the application domain and in the society at large

Examples of thesis topics:

  • Internet of Things Platform Interchangeability with Radiation Meter
  • Embedded System Design of Touch Panel Screen for IoT Applications
  • Task Migration Implement for Fault-Aware Resource Management of Networked Many-Core Systems
  • Hybrid Memory for Next Generation Chip
  • Interoperability Solutions for IoT Protocols via Intelligent Gateway
  • Parallelization of Sorting Algorithms with GPU
  • Embedded Service Bus for Internet of Things Interoperability

Co-operation with other parties

The laboratory of the Programme also participates in the EIT Digital Master School. The Master School is a collaboration with several European technical universities. In the EIT Digital Master School, the laboratory hosts Embedded Systems major’s Internet of Things and Energy Efficient Computing specialisation track.

EIT Digital is a leading European digital innovation and entrepreneurial education organisation. Its goal is to drive Europe’s digital transformation. For more information, see https://masterschool.eitdigital.eu/programmes/es/

Competence description

You will be offered multidisciplinary education which addresses systematic design of embedded systems from both hardware and software perspective.

In the Programme, you will:

  • gain profound knowledge in the field of embedded computing
  • learn to model, design and verify advanced embedded solutions
  • gain understanding of the factors that influence hardware/software tradeoffs
  • learn to carry out research in the field, analyse research results and perform innovative design tasks
  • gain competences for postgraduate studies in the field of embedded computing

Job options

The employment percentage of those holding an Master of Science (in Technology) degree is high in Finland. The degrees from this Programme cover different topical areas of embedded computing well. The education benefits from co-operation with companies in the region, especially in terms of optional Capstone projects.

Based on the personally planned expertise profile, successful careers in the IT sector as embedded computing experts are achievable both Finland and abroad. Graduates are able to pursue careers in the IT industry as embedded computing specialists and experts.

Possible job titles are:

  • systems architect
  • software architect
  • hardware architect
  • specialist or engineer
  • entrepreneur in embedded or control systems engineering

Career in research

Master of Science degree provides eligibility for scientific postgraduate degree studies. Postgraduate degrees are doctoral and licentiate degrees.

Graduates from the Programme are eligible to apply for a position in the University of Turku Graduate School, UTUGS. The Graduate School consists of 16 doctoral programmes which cover all disciplines and doctoral candidates of the University.

Together with the doctoral programmes, the Graduate School provides systematic and high quality doctoral training. UTUGS aims to train highly qualified experts with the skills required for both professional career in research and other positions of expertise.



Read less
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more

This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

  • Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.
  • You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.
  • You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.
  • We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Programme Outline

The study programme consists of four compulsory and four elective modules. The modules offered by the School of Mathematical Sciences will provide a solid understanding of the principles of mathematical finance. The modules offered within the Schools of Electronic Engineering and Computer Sciences will focus on key aspects of technological implementation.

Full time Study

You will study eight modules in total with an even split across semesters one and two. You will complete a 10,000 word dissertation/research project during semester three.

Full time Study with Industrial Experience

You will study eight modules in total with an even split across semesters one and two. You will complete a 10,000 word dissertation/research project during semester three. Expert staff will support the arrangement of your industrial placement, which will be carried out in the second year of your programme and assessed through the completion of the Industrial Placement Project.

The industrial placement takes place from the September following the taught part of the MSc and is for a maximum of 12 months. It is a student's responsibility to secure their own placement, but the EECS Placement Team will provide support. The Placement Team source and promote suitable opportunities, assist with applications, and with interview preparation.

The industrial placement consists of 8-12 months spent working with an appropriate employer in a role that relates directly to your field of study. The placement is currently undertaken after you have completed and passed the taught component of the degree and submitted your MSc project. The placement will provide you with the opportunity to apply the key technical knowledge and skills that you have learnt in your taught modules, and will enable you to gain a better understanding of your own abilities, aptitudes, attitudes and employment potential. The module is only open to students enrolled on a programme of study with integrated placement.

In the event that you are unable to secure a placement we will transfer you onto the 1 year FT taught programme without the Industrial Experience. This change will also apply to any student visa you hold at the time.

Part time Study

Your programme is delivered across two academic years. You will study four modules in each year of the programme, registering upon two modules per semester to balance your workload.

Our modules are assessed by a mixture of in-term assessment and final examinations. Examinations are held between late April and early June. Dissertations are evaluated in September. Successful completion of the MSc programme will result in the award of the MSc Financial Computing (possibly with Merit or with Distinction).

Structure

Semester 1 - Compulsory

  • ECS793P Introduction to Object-Oriented Programming
  • MTH771P Foundations of Mathematical Modelling in Finance
  • MTH739N Topics in Scientific Computing

Semester 1 - Elective

  • ECS765P Functional Programming
  • ECS765P Big Data Processing
  • ECS708P Machine Learning

Semester 2 - Compulsory

  • MTH777P Financial Programming

Semester 2 - Elective

  • MTH773P Advanced Computing in Finance
  • ECS769P Advanced Object-Oriented Programming
  • ECS786P Parallel Computing
  • MTH774P Portfolio Theory and Risk Management
  • MTH772P Stochastic Calculus and Black Scholes Theory

The Project

Each MSc Financial Computing student is required to complete a 60 credit project dissertation. A typical MSc project dissertation consists of about 30 word-processed pages (10,000 words), securely bound, covering a specific research-level topic in financial computing, usually requiring the student to understand, explain and elaborate on results from one or more journal articles and possibly to implement some industry quality code.

Detailed outlines of each module for MSc Financial Computing are on Queen Mary University of London website.



Read less
Microprocessor manufacturers have recently presented the software industry with its most serious challenge ever, by switching from serial execution architectures clocked at ever-increasing clock rates to ever-more parallel multi-core architectures clocked at a constant (or even decreasing) clock rate. Read more

Microprocessor manufacturers have recently presented the software industry with its most serious challenge ever, by switching from serial execution architectures clocked at ever-increasing clock rates to ever-more parallel multi-core architectures clocked at a constant (or even decreasing) clock rate. The consequences will be profound because parallel computational activities will need to be handled as the norm, rather than the exception; programmers of the future will need skills that are currently possessed by very few, due to the inherent complexities of parallel systems.

This pathway is centred round a core theme, Parallel Computing in the Multi-core Era , that introduces students to the aforementioned complexities, and provides techniques and tools that can alleviate the ensuing problems of correctness, reliability, performance and system management. Subsidiary themes allow students to investigate broader areas in which they might apply their newly learned skills.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

Students following the Multi-Core Computing pathway have all the career options as described for general Advanced Computer Science.

In addition, students following this pathway are well placed for careers in the software industry since they will acquire the necessary skills to design and develop software that makes the most out of state-of-the-art multi-core architectures. This includes the games industry, the financial sector, and all other areas in which high performance computing is key.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with a CEng accredited Bachelors programme.



Read less
This course provides specialist expertise in core neuroinformatics (such as computing and biology) focusing on the development of research skills. Read more

This course provides specialist expertise in core neuroinformatics (such as computing and biology) focusing on the development of research skills. It equips you with the skills to contribute to biologically realistic simulations of neural activity and developments. These are rapidly becoming the key focus of neuroinformatics research.

Newcastle is among the pioneers of neuroinformatics in the UK and hosted the £4m EPSRC-funded CARMEN project for managing and processing electrophysiology data. We are currently involved in a £10m EPSRC/Wellcome Trust-funded project. This is on implantable devices for epilepsy patients. We use computer simulations to inform about the stimulation location and protocol.

As the amount of data in the neurosciences increases, new tools for data storage and management are needed. These tools include cloud computing and workflows, as well as better descriptions of neuroscience data. Available data can inform computer simulations of neural dynamics and development. Parallel computing and new algorithms are needed in order to run large-scale simulations. There is high demand within academia as well as within industry involving healthcare informatics, brain-inspired computing, and brain-inspired hardware architectures.

The course is designed for students who have a good degree in the biological sciences (including medicine) or the physical sciences (computer science, mathematics, physics, engineering).

You will gain foundational skills in bioinformatics together with specialist skills such as computing programming, mathematics and molecular biology with a significant focus on the development of research skills.

We provide a unique, multidisciplinary experience that is essential for understanding neuroinformatics. The course draws together the highly-rated teaching and research expertise of our Schools of Computing Science, Mathematics and Statistics, Biology, Cell and Molecular Biosciences and The Institute of Neuroscience. We also have strong links with the International Neuroinformatics Coordinating Facility (INCF).

Research is a large component of this course. The emphasis is on delivering the research training you will need in the future to effectively meet the demands of industry and academia. Newcastle's research in life sciences, computing and mathematics is internationally recognised.

The teaching staff are successful researchers in their field and publish regularly in highly-ranked systems neuroinformatics journals. Find out more about the neuroinformatics community at Newcastle University.

Graduates of this course may want to apply for PhD studies at the School of Computing Science. In the past, all graduates have continued their career as PhD students either at Newcastle University or elsewhere.

Our experienced and friendly staff are on hand to help you. You gain the experience of working in a team in an environment with the help, support and friendship of fellow students.

Project work

Your five month research project gives you real research experience in neuroinformatics. You will have the opportunity to work closely with a leading research team in the School and there are opportunities to work on industry lead projects. You will have one-to-one supervision from an experienced member of the faculty, supported with supervision from associated senior researchers and industry partners as required.

The project can be carried out:

-With a research group at Newcastle University

-With an industrial sponsor

-With a research institute

-At your place of work.

Delivery

The course is based in the School of Computing Science and taught jointly with the School of Mathematics and Statistics and the School of Biology, and the institutes of Cell and Molecular Biosciences, Genetic Medicine and Neuroscience.

We cater for students with a range of backgrounds, including Life Sciences, Computing Science, Mathematics and Engineering. Half of the course is taught and the remainder is dedicated to a research project. Our course structure is highly flexible. You can tailor your degree to your own skills and interests.

Semester one contains modules to build the basic grounding in, and understanding of, neuroinformatics theory and applications, together with necessary computational and numeric understanding to undertake more specialist modules next semester. Training in mathematics and statistics is also provided. Some of these modules are examined in January at the end of semester one.

Semester two begins with two modules that focus heavily on introducing subject-specific research skills. These two modules run sequentially, in a short but intensive mode that allows you time to focus on a single topic in depth. In the first semester two module, you will focus on learning about modelling of biochemical systems - essential material for understanding neural systems at a molecular level. The second module is selected from a number of options. There are up to four modules to choose from, allowing you to tailor the research training component of your degree to your preferences.

Accreditation

We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.

You will have dedicated computing facilities in the School of Computing. You will have access to the latest tools for system analysis and development. For certain projects, special facilities for networking can be set up.

You will enjoy access to specialist IT facilities to support your studies and access to a Linux based website that you can customise with PHP hosting services.



Read less
You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research. Read more

You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.

Our staff have a wealth of expertise across all areas of HPC, parallel programming technologies and data science.

This MSc programme has a strong practical focus and provide access to leading- edge HPC systems such as ARCHER, which is the UK’s largest, fastest and most powerful supercomputer, with more than 100,000 CPU cores.

Data science involves the manipulation, processing and analysis of data to extract knowledge, and HPC provides the power that underpins it.

You will learn the multidisciplinary skills and knowledge in both HPC and data science to unlock the knowledge contained in the increasingly large, complex and challenging data sets that are now generated across many areas of science and business.

Programme structure

This MSc programme takes the form of two semesters of taught courses followed by a dissertation project.

Your studies will have a strong practical focus and you will have access to a wide range of HPC platforms and technologies. You will take seven compulsory courses, which provide a broad-based coverage of the fundamentals of HPC, parallel computing and data science. The option courses focus on specialist areas relevant to computational science. Assessment is by a combination of coursework and examination.

Taught courses

Compulsory courses:

  • Fundamentals of Data Management (Semester 1)
  • Message-Passing Programming (Semester 1)
  • Programming Skills (Semester 1)
  • Threaded Programming (Semester 1)
  • Data Analytics with High Performance Computing (Semester 2)
  • Software Development (Semester 2)
  • Project Preparation (Semester 2)

Optional courses:

  • HPC Architectures (Semester 1)
  • Parallel Numerical Algorithms (Semester 1)
  • Parallel Programming Languages (Semester 1)
  • Advanced Parallel Programming (Semester 2)
  • HPC Ecosystem (Semester 2)
  • Parallel Design Patterns (Semester 2)
  • Performance Programming (Semester 2)
  • Courses from the School of Informatics, Mathematics or Physics (up to 30 credits)

Dissertation

After completing the taught courses, students work on a three-month individual project leading to a dissertation. Dissertation projects may be either research-based or industry-based with an external organisation, with opportunities for placements in local companies.

Industry-based dissertation projects

Through our strong links with industry, we offer our students the opportunity to undertake their dissertation project with one of a wide range of local companies.

An industry-based dissertation project can give you the opportunity to enhance your skills and employability by tackling a real-world project, gaining workplace experience, exploring potential career paths and building relationships with local companies.

Career opportunities

Our graduates are employed across a range of commercial areas, for example software development, petroleum engineering, finance and HPC support. Others have gone on to PhD research in fields that use HPC technologies, including astrophysics, biology, chemistry, geosciences, informatics and materials science.



Read less
Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment. Read more

Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment.

Taught jointly by the School of Computing and the School of Electronic and Electrical Engineering, this course will give you a grasp of all layers needed for mobile communication and computation, from the physical network layer through to the applications that run on mobile devices.

You’ll gain a full understanding of the web and cloud computing infrastructure, as core modules give you a foundation in key topics like systems programming and data communications. A range of optional modules will then allow you to focus on topics that suit your interests and career plans, from cloud computing to embedded systems design and high speed web architecture.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

You’ll take two core modules in Semester 1 that introduce you to fundamental topics like systems programming and network security. With this foundation, you’ll be able to gain high-level specialist knowledge through your choice of optional modules taught by the School of Computing and the School of Electronic and Electrical Engineering.

The optional modules you choose will enable you to direct your studies towards topics that suit your personal interests and career ambitions such as mobile app development, digital media engineering, big data, cloud computing and embedded systems design, among others.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Data Communications and Network Security 15 credits

Optional modules

  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Functional Programming 10 credits
  • Big Data Systems 15 credits
  • Mobile Applications Development 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Cloud Computing 15 credits
  • Graph Theory: Structure and Algorithms 15 credits
  • Communication Network Design 15 credits
  • Optical Communications Networks 15 credits
  • High Speed Internet Architecture 15 credits
  • Digital Media Engineering 15 credits

For more information on typical modules, read Mobile Computing and Communication Networks MSc in the course catalogue

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.Most projects are experimentally based and linked with companies within the oil and gas industry to ensure the topic of research is relevant to the field whilst also addressing a real-world problem.

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Career opportunities are extremely broad, covering jobs in the design of embedded software running on multi-core devices through to jobs involving the design and implementation of new mobile-applications centric systems for business. In the application of mobile computing skills, job opportunities span every area, from the automotive sector through to retail and banking.

You could launch a career in fields such as mobile app development, mobile systems architecture, project management, network consultancy. You could also work as an engineer in embedded mobile communications, network security or research and development among many others – and you’ll even be well-prepared for PhD study.

Careers support

You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual Engineering and Computing Careers Fairs provide further opportunities to explore your career options with some of the UK’s leading employers.

The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.



Read less
The Centre for Doctoral Training in Pervasive Parallelism addresses the most disruptive challenge faced by the computing industry for 50 years. Read more

The Centre for Doctoral Training in Pervasive Parallelism addresses the most disruptive challenge faced by the computing industry for 50 years. Driven by performance and energy constraints, parallelism is now crucial to all layers of the computing infrastructure, from smartphones to globally distributed systems.

This EPSRC-sponsored programme tackles the many urgent interconnected problems raised by parallel systems. How do we design programming languages for such systems? How should the architecture be structured? Which theories, tools and methodologies will allow us to reason about the behaviour of this new hardware and software?

We urgently need answers to these questions to maintain the familiar pace of technological progress, and the benefits it brings to so much of modern life. Spanning theory and practice, the centre addresses this "pervasive parallelism challenge", educating the graduates who will undertake the fundamental research and design required to transform methods and practices. As a pervasive parallelism graduate, you will develop not only deep expertise in your own specialism, but crucially, an awareness of its relationships to other facets of the challenge. These cross-cutting synergies will enable us to unlock the true potential of current and future technologies.

This MSc is the first part of a longer 1+3 (MSc by Research + PhD) programme offered by the School through the EPSRC.

Our supervisors offer internationally leading expertise across all aspects of the pervasive parallelism challenge. These include parallel programming, wireless and mobile networking, reasoning about interaction, models of concurrent computation, energy efficient computing, systems architecture, and performance modelling.

Many more topics can be found be exploring the centre's pages and those of its supervision team and research teams. Most importantly, we believe that key research insights can be made by working across the boundaries of conventional groupings.

Training and support

We offer a four year programme, focused throughout on your development into an independent researcher, under the guidance of an expert supervision team. In the first year, you will undertake a small number of courses, and a large introductory research project, together with a range of sessions on transferable research skills.

Courses are designed to broaden your awareness of pervasive parallelism. Successful students will be awarded a Master of Research degree at this point. From this basis, the subsequent three years will be spent developing and pursuing a PhD research project, under the close supervision of your primary and secondary supervisors.

Our industrial partnerships and engagement programme will ensure that your research is informed by real world case-studies and will provide a source of diverse internship opportunities.

You will have opportunities to take up three- to six-month internships with leading companies in this area, including ARM, Intel, IBM and Microsoft, and to participate in our industrial engagement programme, exchanging ideas and challenges with our sponsor companies at brainstorming and networking events.

The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.

Facilities

You will have access to state-of-the-art facilities from on-chip accelerators including GPGPUs and multicore CPUs to the supercomputer scale systems hosted by the Edinburgh Parallel Computing Centre.

More broadly, the award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.

It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.

Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.

Among our entrepreneurial initiatives is Informatics Ventures, set up to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

We intend for our graduates to become the research leaders, both in industry and academia, whose work will lead the way into the era of mainstream parallelism. This vision is shared by our industrial supporters who have indicated their strong desire to find highly qualified candidates to fill roles in this area. We also have outstanding support for entrepreneurial initiatives through Informatics Ventures.

Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.



Read less
Computer Systems Engineering is a well-established branch of Computer Science, closely related to Electrical Engineering, and concerned with software-hardware integration and the development of high-performance and energy-efficient embedded systems, for example as used in mobile computing. Read more

Computer Systems Engineering is a well-established branch of Computer Science, closely related to Electrical Engineering, and concerned with software-hardware integration and the development of high-performance and energy-efficient embedded systems, for example as used in mobile computing. Aspects covered include questions such as how software can be designed to make use of new, ever more powerful (and often multicore) hardware, or how hardware can be designed to support certain software paradigms. The School of Computer Science is home to internationally renowned research groups working on these challenging tasks, and students following the Computer Systems Engineering pathway will have the opportunity to profit from their understanding of current technology and visions of how to exploit, for example, the formidable complexity of the billion transistor microchips that semiconductor technology will make commonplace over the next decade.

This pathway combines two themes, namely the Parallel Computing in the Mulit-core Era theme and the Mobile Computing theme. The former provides the student with techniques and tools to successfully develop concurrent multicore systems, while alleviating problems of correctness, reliability, performance and system management. The latter provides the student with an understanding of the current state of the art in computing to support mobility for telecommunications.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

The MSc in Advanced Computer Science has an excellent record of employment for its graduates. Opportunities exist in fields as diverse as finance, films and games, pharmaceuticals, healthcare, consumer products, and public services - virtually all areas of business and society. Manchester Computer Science MSc courses are considered among the best in the country and our graduates are actively targeted for the very top jobs in industry and academia.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.



Read less
With the advent of ever more sophisticated and powerful computer environments, the techniques needed to develop and produce the software to run on these systems are themselves becoming increasingly complex. Read more

With the advent of ever more sophisticated and powerful computer environments, the techniques needed to develop and produce the software to run on these systems are themselves becoming increasingly complex. This course is unique in that it combines software engineering with high performance computing, giving you the tools and techniques that employers are looking for and an advantage in the job market.

This specialist option of the MSc Computational and Software Techniques in Engineering offers a unique insight into the development of computer applications across a wide spectrum of modern computing environments, from multi-core CPUs to specialist GPUs to Cloud Computing, all of which are relevant to the IT industry today.

Who is it for?

If you intend to make a career in software development, whether it is in the data centre, on the desktop or in the rapidly expanding mobile application space, you need to have a strong basis in software engineering. This course is unique in that it combines software engineering with high performance computing, giving you the tools and techniques that employers are looking for and an advantage in the job market.

Why this course?

Cranfield University has many years of specialist knowledge and experience in High Performance Computing. We are able to offer a unique insight into the development of computer applications across a wide spectrum of modern computing environments, from multi-core CPUs to specialist GPUs to Cloud Computing, all of which are relevant to the IT industry today.

We introduce students to parallel software development on the desktop, the super-computer and in the Cloud. Each platform has its own challenges and this course ensure that students become familiar with the best approach to writing software for each one.

Cranfield University is very well located for visiting part-time students from all over the world, and offers a range of library and support facilities to support your studies. This enables students from all over the world to complete this qualification whilst balancing work/life commitments. Part-time students have a flexible commencement date.

This Msc programme benefits from a wide range of cultural backgrounds which significantly enhances the learning experience for both staff and students

Course details

The course consists of twelve core modules, including a group design project, plus an individual research project. The course is delivered via a combination of structured lectures, tutorial sessions and computer based workshops.

The C++ and Java programming modules, combined with the Software Engineering course, provide the basis of the academic programme and act as a starting point for the more specialist modules encountered later on. The various computational technology platforms are then introduced, giving students both theoretical and hands-on experience of programming in multi-core, General Purpose CPU, distributed and Cloud computing environments.

Group project

The process of software production is rarely an activity undertaken by an individual developer. In today’s software industry, many different specialists are required to contribute to the creation of software. To ensure a high level of quality in the final product, different roles and responsibilities must be brought together into a single team and therefore clear lines of communication between team members are crucial if the project is to be a success.

An important part of this MSc course is the group project, in which we define a realistic problem and ask each group to propose and implement a solution. It is generally a 6 week project taking place between February and March. Members of each group must decide how to organise themselves, assigning roles to each person.

The group project is an opportunity for you to experience first-hand how a software development team is organised and how the different roles contribute to the final product. This is a chance for you to develop an insight into the organisation of development teams in industry, and allows you to understand what is expected from you once you enter employment.

Part-time students are encouraged to participate in a group project as it provides a wealth of learning opportunities. However, an option of an individual dissertation is available if agreed with the Course Director.

Individual project

The individual research project allows you to delve deeper into an area of specific interest. All projects are based on real research, whether it is an area of interest for members of the department, or as part of an active research project funded by industry. In some cases our industrial partners sponsor specific research projects into real world problems or areas of development that are of direct interest to them. In recent years, students have proposed their own ideas for their research project. You will generally begin to consider the research project after completing 3-4 modules - it then runs concurrently with the rest of your work.

For part-time students it is common that their research thesis is undertaken in collaboration with their place of work.

Assessment

Taught modules 45%, Group project 5%, Individual research project 50%

Your career

The Software Engineering for Technical Computing masters, attracts enquiries from companies all over the world, who wish to recruit high quality software development graduates. There is considerable demand for students with expertise in engineering software development and for those who have strong technical programming skills in industry standard languages and tools.

Graduates of this course are in demand by financial software developers, mobile application developers, commercial engineering software developers, automotive, telecommunications, medical and other industries and research organisations, have been particularly successful in finding long-term employment. We have had positive feedback from companies in industries as diverse as finance to computer games studios. As such, we enjoy excellent employment statistics, with over 95% of graduates employed within six months.

Some students may go on to register for PhD degrees, many, on the basis of their MSc research project. Thesis topics are most often supplied by individual companies on in-company problems with a view to employment after graduation - an approach that is being actively encouraged by a growing number of industries.



Read less
This course is ideal for computing graduates who want to prepare for a general career in IT without the need to specialise at this stage. Read more
This course is ideal for computing graduates who want to prepare for a general career in IT without the need to specialise at this stage.

Subjects range from data modelling, embedded systems and systems architecture to intelligent agents, equipping you to fully understand the application of computing technology in real-world situations whilst gaining the practical business skills that employers seek.

Intermediate qualifications available:

• Postgraduate certificate – 60 credits at Masters level
• Postgraduate diploma – 120 credits at Masters level

There are six entry points through the year. This allows you to start when it is most suitable. The entry points are:

• September
• November
• January
• March
• June
• July

Visit the website: https://www.beds.ac.uk/howtoapply/courses/postgraduate/next-year/computer-science2

Course detail

• Study a broad range of IT disciplines including online database applications, intelligent agents, programming embedded systems, professional project management systems architecture, network systems, distributed and parallel architectures and cryptography and cryptanalysis
• Explore and analyse current trends in the continually expanding area of internet technologies including wireless internet and network configurations and enjoy opportunities to work with innovative distributed environments and architectures
• Develop practical and business skills necessary for a wide range of careers in IT from management to high-level web application development or system administration
• Gain in-depth skills in network management and administration (allowing you to work as a Network Manager) including essential security aspects, grid-computing and fault tolerance
• Benefit from developing expertise equipping you for a career as an IT Consultant, Programmer, Systems/Business Analyst, in web development/web services or in further study on an MSc by Research, MPhil or PhD.

Modules

• Research Methodologies and Project Management
• Network Systems and Administration
• Intelligent Systems and Data Mining
• Distributed and Parallel Computing Technologies
• MSc Project – Computer Science

Assessment

You will be assesses using a combination of written reports, exams, practical (coursework) assignments and computer-based assessment. Coursework assignments typically incorporate formative feedback so that you can gain an insight into whether your work is meeting the necessary targets.

Careers

You will gain valuable skills for a career within Computer Science as well as those relevant for the wider world of IT and business.

The unit ‘Professional Project Management’ requires you to work in a team to apply current project management methodology that embraces all of these knowledge areas in an integrated way while going through the stages of planning, execution and project control.

You will work as part of a team, take responsibility and make autonomous decisions that impact on the project team performance.

Funding

For information on available funding, please follow the link: https://www.beds.ac.uk/howtoapply/money/scholarships/pg

How to apply

For information on how to apply, please follow the link: https://www.beds.ac.uk/howtoapply/course/applicationform

Read less
This course is ideal for computing graduates who want to prepare for a general career in IT without the need to specialise at this stage. Read more
This course is ideal for computing graduates who want to prepare for a general career in IT without the need to specialise at this stage.
Subjects range from data modelling, embedded systems and systems architecture to intelligent agents, equipping you to fully understand the application of computing technology in real-world situations whilst gaining the practical business skills that employers seek.

Intermediate qualifications available:

• Postgraduate certificate – 60 credits at Masters level
• Postgraduate diploma – 120 credits at Masters level

There are six entry points through the year. This allows you to start when it is most suitable. The entry points are:

• September
• November
• January
• March
• June
• July

Visit the website: https://www.beds.ac.uk/howtoapply/courses/postgraduate/next-year/computer-science

Course detail

• Study a broad range of IT disciplines including online database applications, intelligent agents, programming embedded systems, professional project management systems architecture, network systems, distributed and parallel architectures and cryptography and cryptanalysis
• Explore and analyse current trends in the continually expanding area of internet technologies including wireless internet and network configurations and enjoy opportunities to work with innovative distributed environments and architectures
• Develop practical and business skills necessary for a wide range of careers in IT from management to high-level web application development or system administration
• Gain in-depth skills in network management and administration (allowing you to work as a Network Manager) including essential security aspects, grid-computing and fault tolerance
• Benefit from developing expertise equipping you for a career as an IT Consultant, Programmer, Systems/Business Analyst, in web development/web services or in further study on an MSc by Research, MPhil or PhD.

Modules

• Research Methodologies and Project Management
• Network Systems and Administration
• Intelligent Systems and Data Mining
• Distributed and Parallel Computing Technologies
• MSc Project – Computer Science

Assessment

You will be assesses using a combination of written reports, exams, practical (coursework) assignments and computer-based assessment. Coursework assignments typically incorporate formative feedback so that you can gain an insight into whether your work is meeting the necessary targets.

Careers

You will gain valuable skills for a career within Computer Science as well as those relevant for the wider world of IT and business.

The unit ‘Professional Project Management’ requires you to work in a team to apply current project management methodology that embraces all of these knowledge areas in an integrated way while going through the stages of planning, execution and project control. You will work as part of a team, take responsibility and make autonomous decisions that impact on the project team performance.

Funding

For information on available funding, please follow the link: https://www.beds.ac.uk/howtoapply/money/scholarships/pg

How to apply

For information on how to apply, please follow the link: https://www.beds.ac.uk/howtoapply/course/applicationform

Read less
The demand for better products and commercial services drives the search for creative solutions using computing-based systems, and has established a critical dependence between computing and practically every industry and sector. Read more

The demand for better products and commercial services drives the search for creative solutions using computing-based systems, and has established a critical dependence between computing and practically every industry and sector. This flexible programme offers a broad range of advanced study options, reflecting the emerging technologies in industry.

You will be able to shape your programme to match your interests and career ambitions, choosing modules from a range of areas, including the development of human-computer communications (dialogue systems), ubiquitous computing, applying interactive digital multimedia techniques, security and surveillance, and building decision-support tools for uncertain problems in various contexts (e.g. legal, medical, safety). This is a multidisciplinary programme and, in addition to pure computer science modules, you may choose options where computer science intersects with other fields and builds on your first degree.

This programme will:

  • Allow you to personalise your programme through a wide range of employment-relevant module choices.
  • Build your links with industry and potential employers - we have excellent links with industry, working together on commercial and research projects.

Why study your MSc in Computer Science at Queen Mary?

Our research-led approach

Your tuition will be delivered by field leading academics engaged in world class research projects in collaboration with industry, external institutions and research councils.

Our strong links with industry

  • We have collaborations, partnerships, industrial placement schemes and public engagement programmes with a variety of organisations, including Vodafone, Google, IBM, BT, NASA, BBC and Microsoft.
  • Full-time MSc with Industrial Experience option available on our taught MSc programmes. You have the option to complete over two years, with a year of work experience in industry.
  • Industrial projects scheme - To support industrial experience development, you can do your final project in collaboration with an industrial partner.

Full-time

Undertaking a masters programme is a serious commitment, with weekly contact hours being in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.

Part-time

Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.

Important note regarding Part Time Study

We regret that, due to complex timetabling constraints, we are not able to guarantee that lectures and labs for part time students will be limited to two days per week, neither do we currently support any evening classes. If you have specific enquiries about the timetabling of part time courses, please contact the MSc Administrator.

Structure

MSc Computer Science is currently available for one year full-time study, two years part-time study.

Semester 1 - (Maximum of 4 modules to be taken in Semester 1)

Select at least one from:

  •  Functional Programming
  •  Semi-Structured Data and Advanced Data Modelling
  •  Introduction to Object-Oriented Programming

Further options:

  • Machine Learning
  • Introduction to Computer Vision
  • Design for Human Interaction
  • Program Specifications
  • Big Data Processing
  • Introduction to Law for Science and Engineering

Semester 2 - (Maximum of 4 modules to be taken in Semester 2)

Select at least one from:

  •  Security and Authentication 
  •  Interactive Systems Design
  •  Bayesian Decision and Risk Analysis 

Further options from:

  •  Mobile Services
  •  Real Time & Critical Systems
  •  Business Technology Strategy
  •  The Semantic Web
  •  Information Retrieval
  •  Software Analysis and Verification
  •  Natural Language Processing
  •  Advanced Object Oriented Programming
  •  Cloud Computing
  •  Data Analytics
  •  Parallel Computing
  •  Machine Learning for Visual Data Analytics
  • Foundations of Intellectual Property Law and Management

Semester 3

  •  Project

Please note that elective modules are subject to availability, timetabling constraints and may be subject to change.



Read less

Show 10 15 30 per page



Cookie Policy    X