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Masters Degrees (Physical Computing)

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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.



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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 unique course offers critically-engaging themes and technologies, providing skills in immersive storytelling to reflect rapid changes in the games industry. Read more

This unique course offers critically-engaging themes and technologies, providing skills in immersive storytelling to reflect rapid changes in the games industry.

Whether you are looking to build retail or museum installations or you want to use games to tell cinematic stories, this program explores how to craft deeply compelling, critical games and interactive work both for clients and creative practice.

The MA in Independent Games and Playable Experience Design focuses on developing aesthetic awareness, creating compelling mechanics and the ability to craft innovative narratives in games and immersive experiences. Students will be given the skills needed to run a small business and produce quality design on a highly professional level.

Visiting guest lecturers, researchers and artists from around the world will stimulate your critical thinking while inspiring your creativity. Skills based workshops in the latest fabrication and production methodologies will empower you to build stunning installations.

This program will provide access to education and skills new creators will need to be successful in the marketplace.

Why this course?

As technologies have integrated into our everyday lives, elements from games have been woven into everything from the way museums educate the public to how scientists do cancer research. With the rise of mobile, console creators no longer hold a monopoly on gaming platforms. This new found freedom has resulted in an explosion of independent games creating new genres of play. From putting players in immersive augmented worlds to telling transformational personal narratives, these new experiences are redefining the rules of play. Games are now just part of everyday life. As a result, markets that were dominated by traditional media have begun to leverage the ability of games to tell stories, share the news, generate knowledge and educate the public. An explosion of games and apps has created a new breed of entrepreneur which uses small teams to create projects that are accessible to millions. This rising market has become a driving economic reality within the UK.

Modules & structure

Core modules

You will study the following modules:

  • Approaches to Play 1 (15 credits)
  • Approaches to Play 2 (15 credits)
  • Final Projects (60 credits) 

Additionally, a selection of optional modules to the value of 15 and 30 credits will be provided from an annual list for each term and will be made available by the department. 

The current list of optional proposed modules for 2017-2018 is:

  • Introduction to Modelling and Animation (15) 
  • Creative Data (15 Credits) 
  • Workshops in Creative Coding 1 (15 Credits) 
  • Workshops in Creative Coding 2 (15 Credits) 
  • 3D Virtual Environments and Animation (15) 
  • Entrepreneurial Modelling (15) 
  • Physical Computing (30 or 15) 
  • Interactive Fiction (15)

Please note that due to staff research commitments not all of these modules may be available every year.

Option modules

  • Entrepreneurial Modelling (30 credits)
  • Introduction to Modelling and Animation (15 credits)
  • Physical Computing
  • Workshops in Creative Coding 1 (15 credits)
  • Workshops in Creative Coding 2 (15 credits)
  • Interactive Fiction (15 credits)


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Introduction. Applications are invited for an MSc by Research fees funded studentship post commencing 19th March 2018. The Studentship is open to home/EU students. Read more

Introduction

Applications are invited for an MSc by Research fees funded studentship post commencing 19th March 2018. The Studentship is open to home/EU students. It will run for 1 year and the fees of the MSc by Research programme will be paid by the Institute for Sport and Physical Activity Research (ISPAR) at the University of Bedfordshire. 

ISPAR delivers research spanning across sport science, physical activity, health, psychology, behaviour change, pedagogy and social sciences of sport. In the latest Research Excellent Framework assessment 95% of our research was rated as internationally recognised or better. 

About the project

The Institute for Sport and Physical Activity Research (ISPAR) and the Institute for Research in Applicable Computing (IRAC) at the University of Bedfordshire have partnered to deliver this exciting interdisciplinary research project. The project will undertake an evaluation of a mobile phone app and online platform developed by these two research institutes to promote the health and wellbeing of breast cancer patients. The app and online platform are designed to empower patients in their healthcare by encouraging them to self-manage their condition. The tools help to monitor health, medication reminders, medical appointments, physical activity, sedentary behaviour, pain, and fatigue, which are common problems in cancer patients. The app also delivers the patient tips and reminders for healthy behaviours and provides interactive visualisation of the patient’s data, which can be shared with medical professionals to inform clinical decisions. 

The successful candidate will undertake a research project to evaluate the effects of these tools on quality of life, pain, fatigue, physical activity, and sedentary behaviour in breast cancer patients. The candidate will gain research experience in a clinical setting and will work within an interdisciplinary team on this exciting project. It is expected that the student will contribute to the study design, NHS ethical approval process, delivery and evaluation of the intervention, and author a journal publication to disseminate the findings. 

Candidate requirements

The applicant will gain experience in the design, conduct and presentation of research relating to the project. Applicants will have a good first degree (minimum of 2:1) in a relevant discipline (e.g. physical activity, sport and exercise science, applied computing, biomedical science). 

Supervisor:

The student will be under the supervision of: 

- Dr Daniel Bailey Senior Lecturer in Health, Nutrition and Exercise; Institute for Sport and Physical Activity Research 

- Feng Dong Professor in Visual Computing; Institute for Research in Applicable Computing 

Funding: ISPAR will pay the fees of £4,107; there are no bench fees associated with this project. The post will not include a bursary. 

How to apply

For an application pack or any application queries please email  quoting the appropriate reference number. In addition to a CV all applicants will need to send a cover letter with supporting information on their experience and skills and how these relate to the advertised studentship. 

It is expected that interviews will take place the week beginning 26th February 2018. 

For informal discussions or non-application related queries, please contact Dr Daniel Bailey by email at 

Closing date: 19th February 2018 



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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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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.

About this degree

This programme aims to provide a rigorous formal training in computational science 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 Computing

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.

Further information on modules and degree structure is available on the department website: Scientific Computing MSc

Funding

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

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 enables 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 7th in QS World University Rankings 2018). Furthermore, the Thomson Scientific Citation Index shows that UCL is the second-most highly cited European university and 12th 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 enables students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.



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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.

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.



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Why study this programme?. The MSc Computing will help you to develop your computing skills in the theory and practice of designing and developing computer systems. Read more

Why study this programme?

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.

OPPORTUNITIES

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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Provided by the School of Mathematics, this is a one year (full time) taught M.Sc. in High Performance Computing. The degree provides practical training in the emerging high performance computing technology sector. Read more
Provided by the School of Mathematics, this is a one year (full time) taught M.Sc. in High Performance Computing. The degree provides practical training in the emerging high performance computing technology sector.

The aim of the course is to train students in practical applications of high-performance technical computing in industry, finance and research. Course content includes computer architecture, software optimisation, parallel programming, classical simulation and stochastic modelling. Application areas include simulation of physical, chemical and biological systems, financial risk management, telecommunications performance modelling, optimisation and data mining. The course has a number of optional elements, allowing specialization in application areas.

The course includes a strong practical element. Students have unlimited access to a dedicated teaching computing laboratory, and access to the facilities of the Trinity College Centre for High- Performance Computing, which include large-scale parallel computers. Career opportunities include mathematical modeling, simulation and forecasting, database mining and resource management. The techniques covered during the year will allow students to work in advanced software development including parallel and concurrent software applications. High-performance technical computing methods are becoming increasingly widespread in research into mathematics, physics, chemistry and biotechnology, engineering and finance, providing a wide range of options for the student wishing to go on to further research.

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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

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.



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This course in Industrial Physical Biochemistry provides graduates with an advanced knowledge and understanding of physical biochemistry, with particular relevance to industry. Read more
This course in Industrial Physical Biochemistry provides graduates with an advanced knowledge and understanding of physical biochemistry, with particular relevance to industry. Focusing upon technical knowledge and practical skills, the course is ideal for those wishing to pursue careers in research or develop a leading career in the field of physical biochemistry.

Specialist facilities in the School relevant to Industrial Physical Biochemistry include analytical ultracentrifugation, light scattering, protein and carbohydrate biochemistry, and access to Surface Plasmon Resonance, Atomic Force Microscopy, Fluorescence, X-ray crystallography and NMR facilities.

Computing facilities within the School are excellent. Advice on mathematical analysis, statistical design and computer programming is provided.

You will undertake a taught module (Fundamentals of Biomolecular Science) during the autumn semester with lectures, tutorials and a practical. The research module takes place from the start of the course (late September) until the end of August the following year. This is an opportunity to complete a major piece of independent research under the supervision of a member of academic staff. The project can be undertaken wholly or partially in an industrial company’s laboratory in any field of physical biochemistry. There are also two generic training modules.

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This two-year Msc degree in Embedded Computing Systems allows you to study at two locations, choosing from the unique strengths of University of Southampton (system on chip electronics), Kaiserslautern University (embedded systems) and the Norwegian University of Science and Technology in Trondheim (electronics and communication). Read more

This two-year Msc degree in Embedded Computing Systems allows you to study at two locations, choosing from the unique strengths of University of Southampton (system on chip electronics), Kaiserslautern University (embedded systems) and the Norwegian University of Science and Technology in Trondheim (electronics and communication).

Introducing your degree

Develop a thorough understanding of some of the most important technologies that are transforming our communications systems.

Overview

The European Masters in Embedded Computing Systems (EMECS) is a two-year programme run in conjunction with Kaiserslautern University and the Norwegian University of Science and Technology at Trondheim.

You will benefit from Southampton’s expertise in system on chip and electronics, Trondheim’s knowledge of electronics and communications and Kaiserslautern’s strong track record in embedded systems.

The curriculum consists of a core programme, an elective programme and a Masters thesis.

  • The core programme covers the fundamentals of embedded computing systems and offers an equivalent education in all three institutions.
  • The elective programme reflects the specific profiles of the participating partner universities and their associated research institutes.

View the programme specification document for this course

Career Opportunities

Our graduates go on to work as architects of hardware and/or software systems, or as specialists in design methodology or gain employment in companies involved in system-on-chip design, telecommunications, automotive systems and manufacturing.

Graduates from our MSc programme are employed worldwide in leading companies at the forefront of technology. ECS runs a dedicated careers hub which is affiliated with over 100 renowned companies like IBM, Arm, Microsoft Research, Imagination Technologies, Nvidia, Samsung and Google to name a few.  Visit our careers hub for more information.

Through an extensive blend of networks, mentors, societies and our on-campus startup incubator, we also support aspiring entrepreneurs looking to build their professional enterprise skills. Discover more about enterprise and entrepreneurship opportunities.



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Study a degree which develops your arts practice through the expressive world of creative computation. The Masters provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition. Read more

Study a degree which develops your arts practice through the expressive world of creative computation. The Masters provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition.

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.

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 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.

Should I study the MFA or MA Computational Arts?

As well as the MFA, we also offer an MA in Computational Arts. The MA is 1 year (full-time), the MFA 2 years (full-time).

The first year of the MFA is identical to the MA. You take the same classes and you learn the same things. The differences between the two courses is that in the MFA you get a 2nd year in which you take additional courses which help you develop your arts practice further. These courses mean that you get a space to work under a tutor's supervision.

Modules & structure

Year 1

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

The follwing are core modules:

You may then pick modules of your own choice from the optional modules listed below: 

In year 2 you will study the following: 

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.

Find out more about employability at Goldsmiths



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