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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

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This course runs in Germany. This course covers a range of essential topics related to distributed computing systems. Yet these modules are not isolated; each one takes its place in the field in relation to others. Read more

About the course

This course runs in Germany.

This course covers a range of essential topics related to distributed computing systems. Yet these modules are not isolated; each one takes its place in the field in relation to others.

The emphasis in the course is to build the connections between topics, enabling software engineers to achieve co-operation between distinct autonomous systems under constraints of cost and performance requirements.

The course is suitable for:

Recent graduates in Electrical or Electronic Engineering or Computer Science, who wish to develop their skills in the field of distributed computing systems.
Practicing engineers and computer professionals who wish to develop their knowledge in this area.
People with suitable mathematical, scientific or other engineering qualifications, usually with some relevant experience, who wish to enter this field.

Aims

The past few years have witnessed that Grid computing is evolving as a promising large-scale distributed computing infrastructure for scientists and engineers around the world to share various resources on the Internet including computers, software, data, instruments.

Many countries around the world have invested heavily on the development of the Grid computing infrastructure. Many IT companies have been actively involved in Grid development. Grid computing has been applied in a variety of areas such as particle physics, bio-informatics, finance, social science and manufacturing. The IT industry has seen the Grid computing infrastructure as the next generation of the Internet.

The aim of the programme is to equip high quality and ambitious graduates with the necessary advanced technical and professional skills for an enhanced career either in industry or leading edge research in the area of distributed computing systems.

Specifically, the main objectives of the programme are:

To critically appraise advanced technologies for developing distributed systems;
To practically examine the development of large scale distributed systems;
To critically investigate the problems and pitfalls of distributed systems in business, commerce, and industry.

Course Content

Compulsory Modules:

Computer Networks
Network Security and Encryption
Distributed Systems Architecture
Project and Personal Management
High Performance Computing and Big Data
Software Engineering
Embedded Systems Engineering
Intelligent Systems
Dissertation

Special Features

Electronic and Computer Engineering is one of the largest disciplines in the University, with a portfolio of research contracts totalling £7.5 million, and has strong links with industry.

The laboratories are well equipped with an excellent range of facilities to support the research work and courses. We have comprehensive computing resources in addition to those offered centrally by the University. The discipline is particularly fortunate in having extensive gifts of software and hardware to enable it to undertake far-reaching design projects.

We have a wide range of research groups, each with a complement of academics and research staff and students. The groups are:

Media Communications
Wireless Networks and Communications
Power Systems
Electronic Systems
Sensors and Instrumentation.

Women in Engineering and Computing Programme

Brunel’s Women in Engineering and Computing mentoring scheme provides our female students with invaluable help and support from their industry mentors.

Accreditation

Distributed Computing Systems Engineering is accredited by the Institution of Engineering and Technology (IET).

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MA Interaction Design Communication is a practice-led design course that prepares students to design for an increasingly technologically informed and interdisciplinary design world with skills in the following areas. Read more

Introduction

MA Interaction Design Communication is a practice-led design course that prepares students to design for an increasingly technologically informed and interdisciplinary design world with skills in the following areas: interaction design, design prototyping, physical computing, user centered design, open source digital platforms, design research, foresight and insight, experience design, communication design, speculative and critical design, interactive design and digital arts.

Content

MA Interaction Design Communication provides an opportunity for experimental practice in an area of design that increasingly explores the intersection of the physical and digital domains. With a focus on synthesising thought through rigorous design prototyping (making), digital processes and user perspectives, the course is highly reflective of interdisciplinary practice within the contemporary design, media and communications industries.

The integrated approach of the course to critical thinking provides you with the opportunity to work with critical ideas in an applied design context – for example psycho-geographic practice as empirical research or engaging with other critical theories of space to generate user perspectives. This ensures that ideation processes take on both the macro as well as micro opportunities for innovation and speculation crucial to building a portfolio of highly engaged work.

As well as placing you in a position to work across the board spectrum of interaction, design and communication the course is just as interested in design questions as design answers. This means that the course also prepares you for progression to further design research at MPhil/PhD level as well as to advanced self-directed experimental practice.

LCC has an outstanding team of practitioners and published researchers and enjoys a powerful programme of visiting speakers. The course also benefits from a cross-European collaboration with design industry professionals and higher education institutions and there is an opportunity to visit at least one other centre in Europe during the course.

Structure

Phase 1

1.1 Theories and Technologies of Interaction Design (40 credits)
1.2 Research Practice and Human Centered Design (20 credits)

Phase 2

2.1 Interaction Futures and Speculative Design (40 credits)
2.2 Physical Computing and Design Prototyping (20 credits)

Phase 3

Unit 3.1 Final Major Research Project

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This studio based program develops your arts practice through the expressive world of creative computation. It provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition. Read more
This studio based program develops your arts practice through the expressive world of creative computation. It provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition. It is delivered by Computing with contributions from the Centre for Cultural Studies- http://www.gold.ac.uk/pg/mfa-computational-arts/

What is computational art?

Computation consists of all the changes brought about by digital technology. Art is an open set of ways of acting inventively in culture. Mixing the two together in a systematic way gives us computational art. This is a very open field, and one that is set to expand enormously in the coming years. It is where the most exciting developments in technology and in culture can already be found. This degree will place you in the middle of this fast-evolving context.

Follow the links in the student profiles section for work produced by our graduates

What will I learn?

This degree develops your arts practice through the expressive world of creative computation. Over a two years (full-time) or four years (part-time) you will develop your artistic work and thinking through the challenge of developing a series of projects for public exhibition which will explore the technological and cultural ramifications of computation.

You will learn the fundamentals of programming and how to apply this knowledge expressively. You will work with popular open source programming environments such as Processing, OpenFrameworks, P5.js and Arduino, and will learn how to program in languages such as Java, Javascript and C++.

Since computational artworks don’t necessarily involve computers and screens, we also encourage students to produce works across a diverse range of media. Supported by studio technicians in state-of-the-art facilities, our students are producing works using tools such as 3D printers, laser cutters, robotics, wearable technologies, paint, sculpture and textiles.

You will also study contextual modules on computational art and the socio-political effects of technology. Modules in the Centre for Cultural Studies provide students with the historical foundations, frameworks, critical skills and confidence to express their ideas effectively. You will have the opportunity to learn the cultural histories of technology, to reflect on computation in terms of its wider cultural effects, and to understand the way in which art provides rigorous ways of thinking.

Through our masterclass series, we regularly invite world-class artists and curators to explain their work and engage in critical dialogue with the students. This allows you to develop a wider understanding of the contemporary art scene and how your work sits within the professional art world.

Contact the department

If you have specific questions about the degree, contact Theo Papatheodorou.

Modules & Structure

Year 1 shares the same core learning as our MA in Computational Arts programme:

Programming for Artists 1- 15 credits
Programming for Artists 2- 15 credits
Workshops in Creative Coding 1- 15 credits
Final Project in Computational Arts- 60 credits
Physical Computing
Interactive Media Critical Theory- 15 or 30 credits
Physical Computing: Arduino and Related Technologies- 30 credits

In Year 2 you will study the following:

Studio Practice- 120 credits
Computational Arts Critical Studies- 60 credits

Assessment

In Year 2 you will be assessed by: self-evaluation report of 2,500 words; essay of up to 6,000 words; viva voce; exhibition of final work.

Skills & Careers

The programme will equip you with a broad training in the use of creative computing systems that are currently most important in artistic, design and cultural practices and the creative industries, as well as technologies that are yet to emerge.

Funding

Please visit http://www.gold.ac.uk/pg/fees-funding/ for details.

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Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Read more
Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Your research will be supported by an experienced computer scientist within a research group and with the support of a team of advisers.

Research supervision is available under our six research areas, reflecting our strengths, capabilities and critical mass.

Advanced Model-Based Engineering and Reasoning (AMBER)

The AMBER group aims to equip systems and software engineering practitioners with effective methods and tools for developing the most demanding computer systems. We do this by means of models with well-founded semantics. Such model-based engineering can help to detect optimal, or defective, designs long before commitment is made to implementations on real hardware.

Digital Interaction Group (DIG)

The Digital Interaction Group (DIG) is the leading academic research centre for human-computer interaction (HCI) and ubiquitous computing (Ubicomp) research outside of the USA. The group conducts research across a wide range of fundamental topics in HCI and Ubicomp, including:
-Interaction design methods, eg experience-centred and participatory design methods
-Interaction techniques and technologies
-Mobile and social computing
-Wearable computing
-Media computing
-Context-aware interaction
-Computational behaviour analysis

Applied research is conducted in partnership with the DIG’s many collaborators in domains including technology-enhanced learning, digital health, creative industries and sustainability. The group also hosts Newcastle University's cross-disciplinary EPSRC Centre for Doctoral Training in Digital Civics, which focusses on the use of digital technologies for innovation and delivery of community driven services. Each year the Centre awards 11 fully-funded four-year doctoral training studentships to Home/EU students.

Interdisciplinary Computing and Complex BioSystems (ICOS)

ICOS carries out research at the interface of computing science and complex biological systems. We seek to create the next generation of algorithms that provide innovative solutions to problems arising in natural or synthetic systems. We do this by leveraging our interdisciplinary expertise in machine intelligence, complex systems and computational biology and pursue collaborative activities with relevant stakeholders.

Scalable Computing

The Scalable Systems Group creates the enabling technology we need to deliver tomorrow's large-scale services. This includes work on:
-Scalable cloud computing
-Big data analytics
-Distributed algorithms
-Stochastic modelling
-Performance analysis
-Data provenance
-Concurrency
-Real-time simulation
-Video game technologies
-Green computing

Secure and Resilient Systems

The Secure and Resilient Systems group investigates fundamental concepts, development techniques, models, architectures and mechanisms that directly contribute to creating dependable and secure information systems, networks and infrastructures. We aim to target real-world challenges to the dependability and security of the next generation information systems, cyber-physical systems and critical infrastructures.

Teaching Innovation Group

The Teaching Innovation Group focusses on encouraging, fostering and pursuing innovation in teaching computing science. Through this group, your research will focus on pedagogy and you will apply your research to maximising the impact of innovative teaching practices, programmes and curricula in the School. Examples of innovation work within the group include:
-Teacher training and the national Computing at School initiative
-Outreach activities including visits to schools and hosting visits by schools
-Participation in national fora for teaching innovation
-Market research for new degree programmes
-Review of existing degree programmes
-Developing employability skills
-Maintaining links with industry
-Establishing teaching requirements for the move to Science Central

Research Excellence

Our research excellence in the School of Computing Science has been widely recognised through awards of large research grants. Recent examples include:
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Cloud Computing for Big Data Doctoral Training Centre
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Digital Civics
-Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC) Research Grant: a £10m project to look at novel treatment for epilepsy, confirming our track record in Systems Neuroscience and Neuroinformatics.

Accreditation

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

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The MSc Computing will help you to develop your computing skills in the theory and practice of designing and developing computer systems. Read more
The MSc Computing will help you to develop your computing skills in the theory and practice of designing and developing computer systems. On this course you will build on your existing skills and develop new skills in order to prepare yourself for employment in the computing industry. This requires an understanding of programming, systems design and evaluation, project management, creative problem-solving and a range of technical skills. You will also have the opportunity to work on a substantial project of your own choice.

You’ll investigate the current trends and research activities in the computing community, and plan, undertake and evaluate a substantial computing project in which you will put into practice and develop your self-management, communication, critical evaluation and technical skills.





There is a mix of compulsory and optional modules. Compulsory modules include Critical Evaluation (20 credits), OO Software Development (20 credits), User-Centred System Design & Evaluation (20 credits), IT Project Management (20 credits), Master’s Project (60 credits). These core modules give you a solid basis in core computing skills and current research. The optional modules build on these and allow deeper understanding in specific topics such as web development, security and design.

To enhance your work experience you will have an opportunity to undertake an industrial placement as part your MSc. This will extend your study time by six to twelve months depending on the length of the placement. Alternatively there are opportunities to choose an industry-based project.

We expect our students to seek employment within a computing environment. This course will provide a framework within which you can take advantage of the opportunities of developing and improving technology to meet business and user needs.

There are opportunities to continue with your studies to MPhil or PhD.

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Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Read more
Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Numerical methods can only play an even more important role in the future as we face even bigger challenges. Therefore, skilled scientific programmers are in high demand in industry and academia and will drive forward much of the future economy.

Degree information

This programme aims to produce highly computationally skilled scientists and engineers capable of applying numerical methods and critical evaluation of their results to their field of science or engineering. It brings together best practice in computing with cutting-edge science and provides a computing edge over traditional science, engineering and mathematics programmes.

Students undertake modules to the value of 180 credits.

The programme consists of six core modules (90 credits), two optional modules (30 credits) and a dissertation/report (60 credits). A Postgraduate Diploma, six core modules (90 credits), two optional modules (30 credits), is also offered.

Core modules
-Computational and Simulation Methods
-Numerical Methods
-Numerical Optimisation
-Research Computing with C++
-Research Software Engineering with Python
-Techniques of High-Performance

Optional modules - options include a wide selection of modules across UCL Engineering and UCL Mathematical & Physical Sciences.

Dissertation/report
All students undertake an independent research project project which culminates in a dissertation of 20,000 words.

Teaching and learning
The programme is delivered through a combination of lectures and hands-on programming and includes a variety of short programming projects, delivered as part of the taught component. Students are encouraged to participate in scientific seminars, for example, weekly seminars at the UCL Centre for Inverse Problems. Assessment is through examinations, assignments, small projects and the dissertation, including a computer programme.

Careers

We expect our graduates to take up exciting science and engineering roles in industry and academia with excellent prospects for professional development and steep career advancement opportunities. This degree enable students to work on cutting-edge real-life problems, overcome the challenges they pose and so contribute to advancing knowledge and technology in our society.

Employability
Students develop a comprehensive set of skills which are in high demand both in industry and academia: professional software development skills including state-of-the-art scripting and compiled languages; knowledge of techniques used in high-performance computing; understanding and an ability to apply a wide range of numerical methods and numerical optimisation; a deeper knowledge of their chosen science subject; oral and written presentational skills.

Why study this degree at UCL?

UCL has a global reputation for excellence in research and is committed to delivering impact and innovations that enhance the lives of people in the UK, across Europe and around the world. UCL is consistently placed in the global top 20 across a wide range of university rankings (currently fifth in QS World University Rankings 2014/15). Furthermore, the Thomson Scientific Citation Index shows that UCL is the 2nd most highly cited European university and 13th in the world.

Our wide-ranging expertise provides opportunities for groundbreaking interdisciplinary investigation. World-leading experts in the field and students benefit from a programme of distinguished visitors and guest speakers in many scientific seminars. In this way a network of collaborators, mentors and peers is created, which students can access in their future career.

This degree has been designed to balance a professional software development and high performance computing skills with a comprehensive selection of numerical mathematics and scientific subjects, culminating in a scientific computing dissertation project. The dual aspect of a science and computing degree enable students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.

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The MSc Computing will help you to develop your computing skills in the theory and practice of designing and developing computer systems. Read more
The MSc Computing will help you to develop your computing skills in the theory and practice of designing and developing computer systems. On this course you will build on your existing skills and develop new skills in order to prepare yourself for employment in the computing industry. This requires an understanding of programming, systems design and evaluation, project management, creative problem-solving and a range of technical skills. You will also have the opportunity to work on a substantial project of your own choice.

You’ll investigate the current trends and research activities in the computing community, and plan, undertake and evaluate a substantial computing project in which you will put into practice and develop your self-management, communication, critical evaluation and technical skills.

LEARNING ENVIRONMENT AND ASSESSMENT

UCLan provides an 'electronic learning' environment to facilitate flexible learning. This environment combines traditional face-to-face lecture/tutorial and practical sessions with additional, resource-rich, online materials allowing you to continue independent learning through a variety of approaches.

Assessment methods will include individual and group assignments, presentation, seminars and examinations.

FURTHER INFORMATION

To enhance your work experience you will have an opportunity to undertake an industrial placement as part your MSc. This will extend your study time by six to twelve months depending on the length of the placement. Alternatively there are opportunities to choose an industry-based project.

We expect our students to seek employment within a computing environment. This course will provide a framework within which you can take advantage of the opportunities of developing and improving technology to meet business and user needs.

There are opportunities to continue with your studies to MPhil or PhD.

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Study for your doctorate or MPhil at Sheffield Hallam’s Cultural, Communication and Computing Research Institute (C3RI). C3RI an inspiringly diverse multidisciplinary group which makes connections between the research traditions of. Read more
Study for your doctorate or MPhil at Sheffield Hallam’s Cultural, Communication and Computing Research Institute (C3RI). C3RI an inspiringly diverse multidisciplinary group which makes connections between the research traditions of: art; design and media production; communication studies; computing; engineering.

The Institute consists of two research centres:
-Art and Design Research Centre.
-Communication and Computing Research Centre.

We provide an environment in which each discipline can develop its own approach to research. At the same time we bring people together on questions that cut across traditional subject boundaries.

For more information, see the website: https://www.shu.ac.uk/study-here/find-a-course/mphilphd-research-degrees--cultural-communication-and-computing-research-institute

Research activity at C3RI

C3RI is Sheffield Hallam University’s largest community of researchers, with over 100 academics, researchers and technical staff. Our work covers basic, strategic and applied research as well as covering research into teaching and learning. Much of it is through partnerships with businesses and professional collaborators.

Research is supported by the Arts and Humanities Research Board, Engineering and Physical Sciences Research Council, the European Union, commercial clients, charitable bodies and government.

We support a PhD research programme with over 40 students. The C3RI also maintains many knowledge transfer partnerships that support close collaboration between academics, researchers and industrial partners.

Design Futures

C3RI also houses Design Futures – a Yorkshire Forward Centre of Industrial Collaboration for Product and Packaging innovation.
Design Futures has had specialist design teams working exclusively on commercial consultancy services for several years. These teams have developed award winning, innovative solutions for many clients, some of which have been patented.

Course structure

Note: this MPhil can be developed into a PhD. See website for more information: https://www.shu.ac.uk/study-here/find-a-course/mphilphd-research-degrees--cultural-communication-and-computing-research-institute
PhD by confirmation – 3-4 years full time, or 5-7 years part-time.
MPhil – 2 years full time, or 3 years part time.
Start dates – September, January or May.

Master of Philosophy (MPhil)
-Candidates are required to critically investigate and evaluate an approved topic, to demonstrate an understanding of research methods appropriate to their chosen field and to present and defend a thesis by oral examination.

Supervision
Each student is allocated a director of studies and a supervisor. Regular meetings between the student and supervisors are scheduled, with targets set for written and oral presentation of research progress.

Research training
All students are required to complete research training modules unless already studied as part of a masters degree. This has fee implications for part-time students, but is included in the full-time fee. Training is followed by theoretical and textual research, analysis and writing, working closely with the supervisors. Students are expected to present seminar papers on their work and to submit written papers for comment. Students will also be expected to attend relevant seminars from the research seminar series.

Assessment: thesis followed by oral examination.

Other admission requirements

Overseas applicants from countries whose first language is not English must normally produce evidence of competence in English. An IELTS score of 6.0 with 5.5 in all skills (or equivalent) is the standard for non-native speakers of English. If your English language skill is currently below an IELTS score of 6.0 with a minimum of 5.5 in all skills we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English level. The final thesis must be presented in English.

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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

-Newly refurbished computing labs furnished with modern desktop computers
-Access to world leading academic staff
-Collaborative working labs complete with specialist computing and audio visual equipment to support group working
-Over 300 Computers in the School dedicated exclusively for the use of our students
-An Advanced Interfaces Laboratory to explore real time collaborative working
-A Nanotechnology Centre for the fabrication of new generation electronic devices
-An e-Science Centre and Access Grid facility for world wide collaboration over the internet
-Access to a range of Integrated Development Environments (IDEs)
-Specialist electronic system design and computer engineering tools

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.

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.

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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.

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