Masters Degrees (Computation)

The MRes is a Masters degree by research. This means that you are taught core principles and then develop these skills by doing interesting, innovative research, supported by academic staff and peers. This is structured so that you learn how to plan, organise and manage your time; you learn what it is to be a scientific researcher; you help contribute to the development of new knowledge; you learn intellectual skills such as argumentation, exposition, and reasoning; and you develop as an individual by improving your communication skills, writing, collaborative working and creativity.

The programme is designed for highly competent students who are keen on research-oriented Masters programmes. It consists of a mini-project in the first semester and a major research project, which will be two-thirds of the entire Masters programme. You will also study essential Research Skills, and a further 20 credits of optional modules from the following list:

Introduction to Evolutionary Computation
Introduction to Neural Computation
Intelligent Robotics (Extended)
Intelligent Data Analysis (Extended)
Planning (Extended)

Breakdown of course

Natural computation is the study of computational systems that use ideas and gain inspiration from natural systems, including biological, ecological and physical systems. It is an emerging interdisciplinary area in which appropriate techniques and methods are studied for dealing with large, complex, and dynamic problems. The aims of this programme are to:

Meet the increasing need from industry for graduates equipped with knowledge of natural computation techniques.
Provide a solid foundation in natural computation for graduates to pursue a research and development career in industry or to pursue further studies (e.g. PhD).
Give up-to-date coverage of current topics in natural computation (such as evolutionary algorithms, co-evolution, evolutionary design, nature-inspired optimisation techniques, evolutionary games, novel learning algorithms, artificial neural networks, theory of natural computation).

About the School of Computer Science

The School of Computer Science at University of Birmingham has consistently been ranked in the Top 10 in UK league tables and has regularly achieved high satisfaction scores in National Student Surveys. 95% of our students go into graduate employment (Destination of Leavers from Higher Education Survey 2014/15), and our School is ranked 8th nationally for research quality in the '2014 Research Excellence Framework'.
Our work is regularly presented in international conferences and journals, indicating the high standards we achieve in research. In 2008, the UK Funding Councils undertook a national assessment of the quality of research at British universities, the RAE. Among 81 submissions nationally for computer science, the School is equal 7th in the proportion of 4* awards, for research quality that is world-leading in terms of originality, significance and rigour.

Funding and Scholarships

There are many ways to finance your postgraduate study at the University of Birmingham. To see what funding and scholarships are available, please visit: http://www.birmingham.ac.uk/postgraduate/funding

Open Days

Explore postgraduate study at Birmingham at our on-campus open days.
Register to attend at: http://www.birmingham.ac.uk/postgraduate/visit

Virtual Open Days

If you can’t make it to one of our on-campus open days, our virtual open days run regularly throughout the year. For more information, please visit: http://www.pg.bham.ac.uk

Read less

Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
On the one hand, the Master’s in Computation in Neural and Artificial Systems addresses how models based on neural information processing can be used to develop artificial systems, probing of human information processing in closed-loop online settings, as well as the development of new machine learning techniques to better understand human brain function.
On the other hand it addresses various ways of modelling and understanding cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics, complexity theory and optimal control theory to neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner. We also look at new groundbreaking areas in the field of AI, like brain computer interfacing and deep learning.

See the website http://www.ru.nl/masters/ai/computation

Why study Computation in Neural and Artificial Systems at Radboud University?
- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- Together with the world-renowned Donders Institute, the Behavioural Science Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.

Some examples of possible thesis subjects:
- Deep learning
Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.

- Brain Computer Interfacing
Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight (which mental states should we decode?) and technical expertise (which measurement systems and decoding algorithms should be used?). A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:
- PhD researcher on bio-inspired computing
- PhD researcher on neural decoding
- PhD researcher on neural information processing
- Machine learning expert in a software company
- Company founder for brain-based computer games
- Hospital-based designer of assistive technology for patients
- Policy advisor on new developments in neurotechnology
- Software developer for analysis and online visual displays of brain activity

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Sweden and the United States.

See the website http://www.ru.nl/masters/ai/computation

Read less

Overview

Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.

Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.

Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.

Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?

This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.

Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
- In the latest independent Research Assessment Exercise, the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Modules

Advanced Techniques for Differential Equations

Computational Linear Algebra

Operations Research and Modelling

Programming for Scientific Computation

Scientific Computation Dissertation

Simulation for Computer Scientists

Stochastic Financial Modelling

Variational Methods

Vocational Mathematics

Data Mining Techniques and Applications

Mathematical Foundations of Programming

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information

Read less

Take advantage of one of our 100 Master’s Scholarships to study Logic and Computation at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Logic is the basis for reasoning about what we can express and compute, having a profound influence in philosophy, linguistics, mathematics, computer science, and electronics. Since the invention of computers, logic has always been the primary source of ideas and techniques for the theoretical and practical development of programming.

Today, as the scope of programming technologies expands, and the horizon of applications widens, research in logic and its applications in software and hardware development is booming. In industry, formal methods are an integral part of system development, e.g., in automotive electronics, avionics, and chip design.

The MRes Logic and Computation course will teach you about advanced techniques in logic and their applications in research problems in computer science. You will receive an elite education of direct relevance to research and development problems in contemporary information and communication technology (ICT).

Key Features

Teaching score of Excellent.

Highest percentage of top-class researchers of any Computer Science department in Wales – and only 12 in the UK have higher.

70% of the research activity assessed as world-leading or internationally excellent.

Our industrial programme IT Wales which can arrange vacation employment placements.

A state-of-the-art education.

Friendly staff, committed to the highest standards.

A university with high success rate, low drop-out rate, and excellent student support.

Swansea's Library spends more per student on books and other resources than any other university in Wales, and most in the UK.

Course Content

Research Component

The main part of the MRes in Logic and Computation is a substantial and challenging project involving cutting edge research. The completion of such a project will give you the ability and confidence to pursue a successful career in industrial research and development, or to proceed to academic PhD studies.

Taught Component

In seminars and reading courses you will enter the world of research by studying general topics in theoretical computer science as well as special topics for your research project. Guided by your supervisor you will conquer new technical subjects and learn to critically assess current research.
Lecturers and students will meet regularly to discuss recent developments and give informal talks. Topics of the seminars are chosen in accordance with the research projects, and will cover material such as:

Theorem proving techniques
Formal program verification
Algebraic and coalgebraic specification
Modelling of distributed systems
Advanced methods in complexity theory
Additionally you will choose selected taught modules covering important topics such as Critical Systems, IT Security, Concepts of Programming
Languages, Artificial Intelligence Applications, Design Patterns and Generic Programming.

Facilities

The Department is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

90% of Swansea’s Computer Science graduates are in full-time employment or further study within six months of graduating (HESA June 2011).

Some example job titles from the HESA survey 2011:

Software Engineer: Motorola Solutions

Change Coordinator: Logica

Software Developer/Engineer: NS Technology

Workflow Developer: Irwin Mitchell

IT Developer: Crimsan Consultants

Consultant: Crimsan Consultants

Programmer: Evil Twin Artworks

Web Developer & Web Support: VSI Thinking

Software Developer: Wireless Innovations

Associate Business Application Analyst: CDC Software

Software Developer: OpenBet Technologies

Technical Support Consultant: Alterian

Programming: Rock It

Software Developer: BMJ Group

Research

The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

Read less

The Architectural Computation MRes offers a self-directed route which concentrates on research skills, for those intending to take a doctoral degree or those looking to take their existing architecture and computating experience to a higher level. The programme can be taken alone or as the first year of the EngD VEIV.

Degree information

On completion of the programme, students will be able to use computational techniques in architecture, understand and predict the consequences of their design actions through computational processes, integrate their predictions into the design process, and carry out self-sufficient research into new methods and processes.

Students undertake modules to the value of 180 credits.

The programme consists of taught modules (30 credits), research skills modules (30 credits) and research projects (120 credits).

Core modules:
-Computational Analysis
-Computational Synthesis
-Research Skills (A)
-Research Skills (B)
-Computational Research Project

Optional modules - stand-alone MRes students take:
-Extended Personal Research Project
-First-year EngD VEIV students take:
-Interdisciplinary Group Project
-Personal Research Project

Dissertation/report
Students complete project reports for the research projects listed above.

Teaching and learning
The programme is delivered through a combination of lectures, workshops and seminars as well as individual and collaborative projects. Time is dedicated to studio sessions with experienced tutors who have a track record of research into architecture and computation. Assessment is through unseen examination, 3,000-word term paper and project reports.

Careers

After completing the programme, many graduates go on to join leading architectural and engineering practices, either directly with design teams or with specialist modelling groups. In the past three years, graduates have joined Foster and Partners, Zaha Hadid Architects, KPF Associates, Aedas, Arup and Mott MacDonald.

Employability
Our MRes concentrates on your research skills, offering a self-directed route if you are intending to undertake a doctoral degree or are looking to take your existing architecture and computing experience to a higher level. Alumni have joined (or founded) cutting-edge emerging digital design practices such as United Visual Artists and Moving Brands, or they have moved into academic research.

Why study this degree at UCL?

The UCL Bartlett is the UK's largest multidisciplinary Faculty of the Built Environment, bringing together dozens of scientific and professional specialisms required to research, understand, design, construct and operate the buildings and urban environments of the future. Located in London, it is at the heart of the world's largest cluster of creative architects and engineering firms and has all the resources of a world city to hand.

The Architectural Computation programme at UCL offers a unique perspective on the application of technology to the built environment. The course team, drawn from the world-leading Space Syntax Laboratory, comprises both architects and experts in artificial intelligence.

Read less

Summary

The Aerodynamics and Computation programme looks at the fundamentals of aerodynamics as a subject, focusing on numerical methods and the physics and computation of turbulence.
Suitable for those from an engineering, physical sciences or mathematics background who are aiming for advanced specialisation in aerodynamics.

Modules

Compulsory modules: Aerothermodynamics; Advanced Computational Methods I (or Numerical Methods); Applications of CFD; Turbulence: Physics and Modelling; MSc Research Project

Optional modules: further module options are available

Visit our website for further information...

Read less

This postgraduate degree studies the cognitive processes and representations underlying human thought, knowledge and behaviour. It integrates a wide range of disciplines and methodologies with the core assumption that human cognition is a computational process, implemented in neural hardware.

Key topics include: the nature of computational explanation; general principles of cognition; methodology of computational modelling; theories of the cognitive architecture; symbol systems; connectionism; neural computation; and case studies in computational cognitive modelling.

The programme involves intensive training in experimental design and methodology, building computational models and carrying out a substantial piece of original research.

Why study this course at Birkbeck?

Draws on academics from many disciplines, including internationally renowned researchers in psychology, computational modelling and neuroscience.
Good foundation for a research career in the cognitive sciences.
Develops an understanding of core theoretical principles of human thought and an expertise in computer simulation.
Designed for graduates of either the computational sciences or the psychological sciences.
The Department of Psychological Sciences has an outstanding research tradition, with an outstanding international reputation in all aspects of cognitive neuroscience, and especially developmental cognitive neuroscience.
You will have the opportunity to interact with world-class researchers in cognitive neuroscience and cognitive neuropsychology, and attend research seminars organised by the department and a number of other local research centres and institutes.
Psychological Sciences at Birkbeck were ranked 5th in the UK in the 2014 Research Excellence Framework (REF) and we achieved 100% for a research environment conducive to research of world-leading quality.
Psychological research at Birkbeck has ranked 5th in the world in a category of the Best Global Universities Rankings 2016, an important and influential index of research quality.

Our research

Birkbeck is one of the world’s leading research-intensive institutions. Our cutting-edge scholarship informs public policy, achieves scientific advances, supports the economy, promotes culture and the arts, and makes a positive difference to society.

Birkbeck’s research excellence was confirmed in the 2014 Research Excellence Framework, which placed Birkbeck 30th in the UK for research, with 73% of our research rated world-leading or internationally excellent.

Psychological Sciences at Birkbeck were rated 5th in the UK in the 2014 Research Excellence Framework (REF) and we achieved 100% for a research environment conducive to research of world-leading quality.

Read less

Why is this course for you?

•This course is for you if you wish to enter knowledge-led industrial sectors or to embark upon doctoral interdisciplinary study.
•This interdisciplinary programme between Mathematics, Engineering, Physics, and Astronomy gives you access to a broad range of knowledge and application in industry and academia.

What will you gain as a student?

•practical skills in computation in a range of languages and professional software
•rigorous understanding of the theory of common numerical methods
•technical knowledge in numerical modelling
•exposure to a range of common areas of application

Core Modules

Scientific Computing
Practical Programming
Computational Methods for PDEs or Finite Element Methods

Optional Modules include:

Topics in Mathematical Biology
Particle Methods in Scientific Computing
Advanced Fluid Dynamics
Data Mining and Neural Networks
Computational Fluid Dynamics
Dynamics of Mechanical Systems
Applications in Theoretical Physics

Read less

The Architectural Computation MSc provides a comprehensive understanding of the skills required to create generative, emergent and responsive forms, through exposure to real programming environments. Taught by architects and experts in artificial intelligence, students benefit from studio sessions with tutors who have experience of research in this field.

Degree information

On completion of the programme, students will be able to use computational techniques in architecture, understand and predict the consequences of their design actions through computational processes, integrate their predictions into the design process, and carry out self-sufficient research into new methods and processes.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), the choice between two streams of optional modules (45 credits) and a built environment report (60 credits). A Postgraduate Diploma (120 credits, full-time nine months) is offered.

Core modules:
-Computational Analysis
-Computational Synthesis
-Design as a Knowledge-Based Process
-Introduction to Programming for Architecture and Design
-Morphogenetic Programming

Optional modules
-Embodied and Embedded Technologies
-Digital Interaction

Dissertation/report
All MSc students submit a 10,000-word report related to the main themes of the programme, typically involving the development of an interactive installation or a system to improve the design process.

Teaching and learning
The programme is delivered through a combination of lectures, workshops and seminars as well as individual and collaborative projects. Assessment is through unseen examination, coursework (including 3000-word essay, learning log, digitally fabricated piece and documentation, short video piece, and physical piece with video documentation) practical exercises and the dissertation.

Careers

First destinations of recent graduates include: Smart Eon Construction, Space Intacts, Prosper and Partners, Foster and Partners, Aedas Architects Ltd, 3D Reid, Squint Opera: 3D-Web designer, RTKL, G and L Architects, HOK, Zaha Hadid Architects and KPF Associates. Alumni have also joined (or founded) cutting-edge emerging digital design practices such as United Visual Artists and Moving Brands, or moved into academic research.

Top career destinations for this degree:
-Architect, Gallop
-Architectural Designer, Vx3
-Computational Designer, Bryden Wood
-Creative Technologist, Hirsch & Mann / Technology Will Save Us
-Design System Analyst, Foster + Partners

Employability
Our MSc provides a full learning experience with set projects and structured learning. It can be taken by those without any computational experience or those looking for industry-applicable skills. After completing the programme, most graduates go on to join leading architectural and engineering practices, either directly with design teams or with specialist modelling groups.

Why study this degree at UCL?

The UCL Bartlett is the UK's largest multidisciplinary Faculty of the Built Environment, bringing together scientific and professional specialisms required to research, understand, design, construct and operate the buildings and urban environments of the future.

Located in London, it is at the heart of a large cluster of creative architects and engineering firms, next to the UK's seat of government and finance and has all the resources of a world city to hand.

The new architecture coming out of the Bartlett is characterised by a high level of invention and creativity. The school is internationally known as a centre for innovative design.

Read less

Robotics and autonomous systems (RAS) are set to shape innovation in the 21st century, underpinning research in a wide range of challenging areas: the ageing population, efficient health care, safer transport, and secure energy. The UCL edge in scientific excellence, industrial collaboration and cross-sector activities make it ideally placed to drive IT robotics and automation education in the UK.

Degree information

The programme provides an overview of robotic and computational tools for robotics and autonomous systems as well as their main computational components: kinetic chains, sensing and awareness, control systems, mapping and navigation. Optional modules in machine learning, human-machine interfaces and computer vision help students grasp fields related to robotics more closely, while the project thesis allows students to focus on a specific research topic in depth.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), two optional modules (30 credits), two elective modules (30 credits), and a dissertation/report (60 credits).

Core modules
-Robotic Control Theory and Systems
-Robotic Sensing, Manipulation and Interaction
-Robotic Systems Engineering
-Robotic Vision and Navigation

Optional modules
-Acquisition and Processing of 3D Geometry
-Affective Computing and Human-Robot Interaction
-Artificial Intelligence and Neural Computing
-Image Processing
-Inverse Problems in Imaging
-Machine Vision
-Mathematical Methods, Algorithmics and Implementations
-Probabilistic and Unsupervised Learning
-Research Methods and Reading
-Supervised Learning
-Other selected modules available within UCL Computer Science
-Students also choose two elective MSc modules from across UCL Computer Science, UCL Medical Physics & Biomedical Engineering, UCL Mechanical Engineering and UCL Bartlett School of Architecture.

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 30,000 words.

Teaching and learning
Teaching is delivered by lectures, tutorials, practical sessions, projects and seminars. Assessment is through examination, individual and group projects and presentations, and design exercises.

Careers

Robotics is a growing field encompassing many technologies with applications across different industrial sectors, and spanning manufacturing, security, mining, design, transport, exploration and healthcare. Graduates from our MSc programme will have diverse job opportunities in the international marketplace with their knowledge of robotics and the underpinning computational and analytical fundamentals that are highly valued in the established and emerging economies. Students will also be well placed to undertake PhD studies in robotics and computational research specific to robotics but translational across different analytical disciplines or applied fields that will be influenced by new robotic technologies and capabilities.

Employability
This programme prepares students to enter a robotics-related industry or any other occupation requiring engineering or analytical skills. Graduates with skills to develop new robotics solutions and solve computational challenges in automation are likely to be in demand globally.

Why study this degree at UCL?

UCL was ranked first in the UK for computer science and informatics in the recent Research Excellence Framework (REF).

With the external project involvement anticipated, students on this programme will have the opportunity to interact and collaborate with key companies in the industry - Airbus, Shadow Hand, OC Robotics and Intuitive Surgical - and work on real-world problems through industry-supported projects.

Recent investment across UCL in the Faculty of Engineering and The Bartlett Faculty of the Built Environment has created the infrastructure for an exciting robotics programme, which will be interdisciplinary and unique within the UK and Europe.

Read less

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.

Read less

This degree 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/ma-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 year (full-time) or two 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

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- N/A

Funding

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

Read less

Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

Our MSc Statistics and Operational Research will appeal if your first degree included mathematics as its major subject, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

You specialise in areas including:
-Continuous and discrete optimisation
-Time series econometrics
-Heuristic computation
-Experimental design
-Machine learning
-Linear models

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

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

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00808&subgroup=2

Our expert staff

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

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our MSc Statistics and Operational Research will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms on our module, Combinatorial Optimisation, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia.

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

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

Example structure

-Nonlinear Programming
-Combinatorial Optimisation
-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Ordinary Differential Equations (optional)
-Graph Theory (optional)
-Partial Differential Equations (optional)
-Portfolio Management (optional)
-Machine Learning and Data Mining (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Applications of Data Analysis (optional)
-Mathematical Research Techniques Using Matlab (optional)

Read less

Programme description

Cognitive Science is a discipline in growing demand, and Edinburgh is a widely recognised leader in this area, with particular strengths in natural language, speech technology, robotics and learning, neural computation and philosophy of the mind.

You will gain a thorough grounding in neural computation, formal logic, computational and theoretical linguistics, cognitive psychology and natural language processing, and through a vast range of optional courses you will develop your own interests in this fascinating field.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a ‘specialist area’ within the programme, which will determine the choice of your optional courses. The specialist areas are:

• Cognitive Science
• Natural Language Processing
• Neural Computation and Neuroinformatics

Compulsory courses:

• Informatics Research Review
• Informatics Research Proposal
• Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
• Dissertation

There are several optional courses to choose from, such as:

• Accelerated Natural Language Processing
• Automated Reasoning
• Computational Cognitive Neuroscience
• Human-Computer Interaction
• Machine Learning and Pattern Recognition
• Natural Language Understanding
• Neural Computation
• Text Technologies for Data Science
• Bioinformatics
• Topics in Cognitive Modelling

Career opportunities

This programme will give you a deep understanding of the expanding domain of cognitive science through formal study and experiments. It is perfect preparation for a rewarding academic or professional career. The quality and reputation of the University, the School of Informatics and this programme will enhance your standing with many types of employer.

Read less

The Quantum Technologies MSc will take students to the cutting-edge of research in the emerging area of quantum technologies, giving them not only an advanced training in the relevant physics but also the chance to acquire key skills in the engineering and information sciences.

Degree information

Students learn the language and techniques of advanced quantum mechanics, quantum information and quantum computation, as well as state-of-the-art implementation with condensed matter and quantum optical systems.

Students undertake modules to the value of 180 credits.

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

Core modules
-Advanced Quantum Theory
-Atom and Photon Physics
-Quantum Communication and Computation
-Research Case Studies for Quantum Technologies
-Transferable Skills in Research Case Studies for Quantum Technologies

Optional modules - students choose three of the following optional modules:
-Advanced Photonic Devices
-Introduction to Cryptography
-Nanoelectronic Devices
-Nanoscale Processing for Advanced Devices
-Optical Transmission and Networks
-Order and Excitations in Condensed Matter
-Physics and Optics of Nano-Structures
-Research Computing with C++
-Research Software Engineering with Python

Dissertation/report
All students undertake an independent research project (experimental or theoretical) related to quantum technologies, which culminates in a presentation and a dissertation of 10,000 words.

Teaching and learning
The programme is delivered through a combination of lectures and seminars, with self-study on two modules devoted to the critical assessment of current research topics and the corresponding research skills. Assessment is through a combination of problem sheets, written examinations, case study reports and presentations, as well as the MSc project dissertation.

Careers

The programme prepares graduates for careers in the emerging quantum technology industries which play an increasingly important role in: secure communication; sensing and metrology; the simulation of other quantum systems; and ultimately in general-purpose quantum computation. Graduates will also be well prepared for research at the highest level in the numerous groups now developing quantum technologies and for work in government laboratories.

Employability
Graduates will possess the skills needed to work in the emerging quantum industries as they develop in response to technological advances.

Why study this degree at UCL?

UCL offers one of the leading research programmes in quantum technologies anywhere in the world, as well as outstanding taught programmes in the subjects contributing to the field (including physics, computer science, and engineering). It also hosts the EPSRC Centre for Doctoral Training in Delivering Quantum Technologies.

The programme provides a rigorous grounding across the disciplines underlying quantum technologies, as well as the chance to work with some of the world's leading groups in research projects. The new Quantum Science and Technology Institute ('UCLQ') provides an umbrella where all those working in the field can meet and share ideas, including regular seminars, networking events and opportunities to interact with commercial and government partners.

Read less