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Masters Degrees (Neural Computation)

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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. Read more

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.



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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. Read more
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

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The School has a strong international reputation for research in this area and this expertise influences this course which explores current research and practice in artificial intelligence and robotics. Read more
The School has a strong international reputation for research in this area and this expertise influences this course which explores current research and practice in artificial intelligence and robotics. This MSc can lead to a career such as a designer of intelligent systems or in research. The core modules are: artificial life with robotics, neural computation and machine learning, theory and practice of artificial intelligence.

Why choose this course?

-This MSc is available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies
-One of a range of advanced courses within our postgraduate Master's programme in Computer Science, this particular course provides you with a specialism in Artificial Intelligence and Robotics
-Advanced topics studied include artificial life with robotics, neural computation and machine learning, theory and practice of artificial intelligence
-Taught by a highly-regarded and long-established computer science department
-Sixty percent of our research impact in Computer Science and Informatics at the University of Hertfordshire has been rated at world-leading or internationally excellent in the Research Excellence Framework (REF) 2014

Careers

Our master's programme is designed to give Computer Science graduates the specialist, up-to-date skills and knowledge sought after by employers, whether in business, industry, government or research.

This particular course will prepare you to take up a challenging job or to pursue further research in specific AI fields. Typical career opportunities include researcher or designer for intelligent systems.

Teaching methods

Classes consist of lectures, small group seminars, and practical work in our well-equipped laboratories. We use modern, industry-standard software wherever possible. There are specialist facilities for networking and multimedia and a project laboratory especially for master's students.

In addition to scheduled classes, you will be expected a significant amount of time in self-study, taking advantage of the extensive and up-to-date facilities. These include the Learning Resource Centres, open 24x7, with 1,500 computer workstations and wifi access, Studynet our versatile online study environment usable on and off campus, and open access to our labs.

Work Placement

All our one year full time Computer Science Masters programmes are available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies.

They offer you the opportunity to work for one year in a highly professional and stimulating environment. You will be a full time employee in a company earning a salary and will learn new skills that can't be taught at University. During the placement, you will be able to gain further insight into industrial practice that you can take forward into your individual project.

We will provide excellent academic and personal support during both your academic and placement periods together with comprehensive careers guidance from our very experienced dedicated Careers and Placements Service.

Although the responsibility for finding a placement is with you, our Careers and Placements Service maintains a wide variety of employers who offer placement opportunities and organise special training sessions to help you secure a placement, from job application to the interview. Optional one-to-one consultations are also available.

In order to qualify for the placement period you must maintain an overall average pass mark of not less than 60% across all modules studied in semester ‘A’.

Structure

Year 1
Core Modules
-Professional Issues
-Investigative Methods for Computer Science
-Artificial Life with Robotics
-Neural Networks and Machine Learning
-Theory and Practice of Artificial Intelligence
-Preparation for Placement
-Professional Work Placement for MSc Computer Science

Optional
-Professional Issues
-Investigative Methods for Computer Science
-Data Mining
-Mobile Standards, Interfaces and Applications
-Human Computer Interaction: Principles and Practice
-Advanced Databases
-Programming Paradigms
-Measures and Models for Software Engineering
-Programming for Software Engineers
-Software Engineering Practice and Experience
-Distributed Systems Security
-Secure Systems Programming
-Network System Administration
-Multicast and Multimedia Networking
-Wireless, Mobile and Ad-hoc Networking
-Information Security, Management and Compliance
-Digital Forensics
-Penetration Testing

Year 2
Core Modules
-Artificial Intelligence with Robotics Masters Project

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Be inspired to innovate and develop the robots, artificial intelligence and autonomous systems of tomorrow’s world. Read more
Be inspired to innovate and develop the robots, artificial intelligence and autonomous systems of tomorrow’s world. Gain advanced theoretical and practical knowledge from our world-leading experts in interactive and intelligent robotics, and graduate ready to pursue an exciting career in anything from home automation to deep sea or space exploration. You’ll also have the opportunity to gain invaluable industry experience and cultivate professional contacts on an integral work placement.

Key features

-Enhance your employability and grow your professional network with an optional integral work placement. You can choose to work in the UK, or overseas in countries including France, Germany or Japan.
-Get up-to-date with the latest developments in artificial life and intelligence, adaptive behaviour, information visualisation, neural computation and dynamic systems, as well as remote access and monitoring systems. Our seminars series with speakers from industry and academia gives you the opportunity to keep ahead in this fast moving field.
-Give yourself the edge. Our programme distinguishes itself from other robotics masters programmes, in the UK and abroad, by ensuring a deeper theoretical and practical knowledge of interactive and intelligent robotics.
-Expand your skills with first-class facilities including 3D rapid prototyping systems, in-house PCB design and assembly tools, and our award winning Plymouth Humanoid robots.
-Get expert training from members of the Marine and Industrial Dynamic Analysis (MIDAS) research group and the Centre for Robotics and Neural Systems (CRNS).
-Become a professional in your field – this programme is accredited by the Institution of Engineering and Technology (IET).
-Benefit by combining disciplines that are traditionally taught separately. You’ll graduate ready with the expertise and joined-up knowledge to design and develop fully integrated mechanical, electronic, control and computing systems.

Course details

On this programme you’ll gain a solid and broad understanding of the latest developments and issues in robotics. You’ll build theoretical and practical knowledge of control and design as well as covering the interface between real-world devices, autonomous processing and evaluation of acquired information. You’ll investigate user interaction and intelligent decision-making and immerse yourself in an innovative project inspired by the latest developments in technology and society. You’ll have access to a robotics club and to a seminar series so that you can keep up-to-date with advances in the industry and academia.

Core modules
-ROCO503 Sensors and Actuators
-BPIE500 Masters Stage 1 Placement Preparation
-PROJ509 MSc Project
-AINT511 Topics in Advanced Intelligent Robotics
-MECH533 Robotics and Control
-SOFT561 Robot Software Engineering
-AINT513 Robotic Visual Perception and Autonomy
-AINT512 Science and Technology of Human-Robot Interaction

Optional modules
-BPIE502 Electrical/Robotics Masters Industrial Placement

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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The Institute for Neuroscience has clinicians and scientists working together to understand the brain and behaviour. Read more
The Institute for Neuroscience has clinicians and scientists working together to understand the brain and behaviour. From the basic biology of neurons through to complex processes of perception and decision-making behaviour, we address how the mind, brain, and body work together and translate this knowledge into clinical applications for patient benefit.

We offer MPhil supervision in the following research areas:

Motor systems development, plasticity and function

We conduct clinical and preclinical studies of normal and abnormal development and plasticity of the motor system. We run functional studies and computer modelling of motor system activity throughout the neuraxis. We also research the development and assessment of novel therapies for motor disorders/lesions including stem cell and brain-machine interface.

Visual system development, plasticity and repair]]
We research the development and assessment of novel neuro-technological approaches to retinal dystrophy repair including brain-machine interface and stem cells. We use in vitro approaches to look at retinal development and visual system wiring.

[[Neural computation and network systems
We conduct experimental and theoretical (computational) studies aimed at understanding how neurones throughout the brain interact in localised networks to compute complex tasks. Our research looks at the role of network activity in a wide range of neurological, neurodegenerative and psychiatric disorders.

Auditory neuroscience

We conduct clinical and preclinical studies aimed at understanding the brain mechanisms involved in detection, discrimination and perception of sound. We are interested in how these mechanisms are affected in individuals with brain disorders, including dementia, autism and stroke.

Pain

Our research focuses on:
-Understanding mechanisms underlying pain, analgesia, and anaesthesia
-The development of methods to assess pain and to alleviate pain in animals and humans

Psychobiology

We conduct studies in laboratory animals, healthy volunteers and patient populations investigating the mechanisms underlying mood, anxiety and addiction disorders and their treatment. Allied research looks at normal neuropsychology, and the physiology and pharmacology of neurotransmitter and endocrine systems implicated in psychiatric disorders.

Neurotoxicology

Our research focuses on delineating the effects and understanding the mechanisms of action of established and putative neurotoxins, including environmental and endogenous chemicals, and naturally occurring toxins.

Forensic psychiatry and clinical psychology

Our research covers:
-The assessment, treatment and management of sex offender risk
-Development and assessment of cognitive models
-Cognitive behavioural therapy (CBT) treatment for bipolar disorder, psychosis, anxiety and developmental disorders
-Developmental disorders of perception and cognition

Systems and computational neuroscience

We conduct theoretical (computational) and experimental studies aimed at understanding the neuroanatomy, neuropharmacology of vision, visual attention and episodic memory.

Behaviour and evolution

Many research groups take an evolutionary and comparative approach to the study of brain and/or behaviour, comparing brain function and behaviour among such disparate groups as insects, birds and mammals, and studying the ecological and evolutionary functions of behaviour. Much of our work is at the forefront of the fields of neuroethology, behavioural ecology and comparative cognition, and has important implications for the study and practice of animal welfare.

Visual perception and human cognition

We research:
-Colour and depth perception - perception of natural scenes
-Psychophysics and attention - memory
-Word learning in children
-Body image dysfunction
-Visual social cognition and face processing
-Advertising and consumer behaviour

Pharmacy

Our new School of Pharmacy has scientists and clinicians working together on all aspects of pharmaceutical sciences and clinical pharmacy.

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Informatics is the study of how natural and artificial systems store, process and communicate information. Read more

Informatics is the study of how natural and artificial systems store, process and communicate information.

Edinburgh has a long-standing tradition of world-class research and teaching in informatics, a discipline central to a new enlightenment in scholarship and learning, and critical to the future development of science, technology and society.

This is our most sought-after taught MSc. We offer a wide choice of courses, spanning established disciplines such as cognitive and computer science as well as emerging areas such as bioinformatics.

The programme takes full advantage of our expertise in research and teaching, including specialisms unique to Edinburgh.

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.

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

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

  • Analytical and Scientific Databases
  • Bioinformatics Systems and Synthetic Biology
  • Cognitive Science, Computer Systems, Software Engineering and High Performance Computing
  • Intelligent Robotics
  • Agents, Knowledge and Data
  • Machine Learning
  • Natural Language Understanding
  • Neural Computation and Neuroinformatics
  • Programming Languages
  • Theoretical Computer Science

There are 100 optional courses available to MSc Informatics students, including courses within specialist areas unique to the programme.

Career opportunities

Our graduates are well regarded by potential employers worldwide. Many go on to work in the technology industry as software engineers, IT consultants, programmers and developers, and may work with the software and hardware giants that have become household names. Others go on to further study and research.



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We offer an opportunity to train in one of the newest areas of biology. the application of engineering principles to the understanding and design of biological networks. Read more

Programme description

We offer an opportunity to train in one of the newest areas of biology: the application of engineering principles to the understanding and design of biological networks. This new approach promises solutions to some of today’s most pressing challenges in environmental protection, human health and energy production.

This MSc will provide you with a thorough knowledge of the primary design principles and biotechnology tools being developed in systems and synthetic biology, ranging from understanding genome-wide data to designing and synthesising BioBricks.

You will learn quantitative methods of modelling and data analysis to inform and design new hypotheses based on experimental data. The University’s new centre, SynthSys, is a hub for world-leading research in both systems and synthetic biology.

Programme structure

The programme consists of two semesters of taught courses followed by a research project and dissertation, which can be either modelling-based or laboratory-based.

Compulsory courses:

Applications of Synthetic Biology
Dissertation project
Information Processing in Biological Cells
Practical Systems Biology
Social Dimensions of Systems and Synthetic Biology
Tools for Synthetic Biology

Option courses:

Biobusiness
Biochemistry
Bioinformatics Algorithms
Bioinformatics Programming & System Management
Biological Physics
Computational Cognitive Neuroscience
Drug Discovery
Economics & Innovation in the Biotechnology Industry
Environmental Gene Mining & Metagenomics
Functional Genomic Technologies
Gene Expression & Microbial Regulation
Industry & Entrepreneurship in Biotechnology
Introduction to Scientific Programming
Molecular Phylogenetics
Neural Computation
Next Generation Genomics
Practical Skills in Biochemistry
Probabilistic Modelling and Reasoning
Statistics and Data Analysis
Stem Cells & Regenerative Medicine

Career opportunities

The programme is designed to give you a good basis for managerial or technical roles in the pharmaceutical and biotech industries. It will also prepare you for entry into a PhD programme.

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The Cognitive and Decision Sciences MSc at UCL studies the cognitive processes and representations underlying human thought, knowledge and decision-making. Read more
The Cognitive and Decision Sciences MSc at UCL studies the cognitive processes and representations underlying human thought, knowledge and decision-making. It integrates a wide range of disciplines and methodologies, with the core assumption that human cognition and choice are computational processes, implemented in neural hardware.

Degree information

Key topics include the nature of computational explanation; the general principles of cognition; the scope of rational choice explanation; probabilistic models of the mind; learning and memory; and applications to economics and business. The programme involves training in experimental design and methodology, building computational models and undertaking original research.

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 research dissertation (60 credits).

Core modules
-Introduction to Cognitive Science
-Principles of Cognition
-Research Statistics
-Research Skills and Programming for Cognitive Science
-Judgement and Decision Making
-Knowledge, Learning and Inference

Optional modules
-Applied Decision-making
-Human Learning and Memory
-Cognitive Neuroscience
-Social Cognition: Research Methods
-The Brain in Action
-Neural Computation: Models of Brain Function
-Consumer Behaviour
-Understanding Individuals and Groups
-Social Neuroscience
-Social Cognition, Affect and Motivation
-Current Issues in Attitude Research
-Talent Management
-Business Psychology Seminars
-Interpretation of Forensic Evidence
-Consulting Psychology
-Designing and Analysing fMRI Experiments

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of approximately 10,000–12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, class presentations, and practical, statistical, computational and experimental class work. Student performance is assessed through online tests, coursework, essays, practical experimental and computational mini-projects, and the dissertation.

Careers

Students have gone on to find employment in the following areas: research, teaching, lecturing, consultancy, finance, and marketing.

For more detailed careers information please visit the department website: http://www.ucl.ac.uk/pals/study/masters/TMSPSYSCDS01

Top career destinations for this degree:
-Managing Director, Temasek International Pte Ltd
-Consumer Behaviour Research Expert, TNS
-Insight Consultant, Kantar World Panel
-Assistant Policy Adviser, Cabinet Office Behavioural Insights Team
-Software Developer, Federal Home Loan Bank of New York

Employability
On completion of the programme, students will have acquired theoretical and empirical knowledge in cognition science and decision-making, and a broad range of practical research skills. They will have made original contributions to this field in their research projects, and will understand how to apply their knowledge to real-world decision problems. They will also have developed various analytical and logical reasoning skills which can be applied to many domains of research and non-academic work. They will, in addition, have an understanding of the philosophical issues underlying cognitive science and neuroscience.

Why study this degree at UCL?

The programme draws on an outstanding faculty, ranging across many disciplines, including internationally renowned researchers in psychology, computational modelling, neuroscience and economics.

London is one of the global hot-spots for research in cognition, decision-making, and neuroscience; and it is an intellectual hub, with a high density of research seminars and scientific meetings that attract leading international researchers.

London is also one of the world's foremost commercial and political centres, with consequent opportunities for high-level applied research; and it is a vibrant, culturally diverse and international city, with world-class music, theatre and galleries.

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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. Read more
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.

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

Who is it for?

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

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

Objectives

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

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

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

Placements

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

Academic facilities

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

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

Scholarships

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

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

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

Teaching and learning

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

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

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

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

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

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

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

Course content

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

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

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

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

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

Individual project - (60 credits)

Career prospects

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

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

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The 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. Read more
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

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Launch yourself into the robotics research environment and develop the skills and confidence to conduct your own in-depth research project. Read more
Launch yourself into the robotics research environment and develop the skills and confidence to conduct your own in-depth research project. Gain current, advanced theoretical and practical knowledge from our world-leading experts in intelligent and interactive robotics. You’ll graduate ready for a future in the fast-moving world of personal and service robotics and with the skills to further your research to PhD level.

Key features

-Immerse yourself in an individual research project and learn how to communicate your motivation, methodology, and conclusions through a formal dissertation and summary paper.
-Get up-to-date with the latest developments in artificial life and intelligence, adaptive behaviour, information visualisation, neural computation and dynamic systems, as well as remote access and monitoring systems. Our seminars series with speakers from industry and academia gives you the opportunity to keep ahead in this fast moving field.
-Give yourself the edge. Our programme distinguishes itself from other robotics masters programmes, in the UK and abroad, by ensuring a deeper theoretical and practical knowledge of interactive and intelligent robotics.
-Expand your skills with first-class facilities including 3D rapid prototyping systems, in-house PCB design and assembly tools, and our award winning Plymouth Humanoid robots.
-Get expert training from members of the Marine and Industrial Dynamic Analysis (MIDAS) research group and the Centre for Robotics and Neural Systems (CRNS).
-Benefit by combining disciplines that are traditionally taught separately. You’ll graduate ready with the expertise and joined-up knowledge to design and develop fully integrated mechanical, electronic, control and computing systems.
-The taught elements of this programme are also delivered to students on Year 1 of the MSc Robotics Technology programme.

Course details

On this programme you’ll gain a solid and broad understanding of the latest developments and issues in robotics. You’ll build advanced theoretical and practical knowledge of control and design as well as covering the interface between real-world devices, autonomous processing and evaluation of acquired information. You’ll learn how to search, critically appraise and identify relevant research literature. You’ll also gain expertise in project management and personal effectiveness whilst immersing yourself in a substantial and innovative project inspired by the latest developments in technology and society. You’ll have access to a robotics club and to a seminar series so that you can keep up-to-date with advances in the industry and academia.

Core modules
-PROJ510 MRes Project

Optional modules
-ROCO503 Sensors and Actuators
-AINT511 Topics in Advanced Intelligent Robotics
-MECH533 Robotics and Control
-SOFT561 Robot Software Engineering
-AINT513 Robotic Visual Perception and Autonomy
-AINT512 Science and Technology of Human-Robot Interaction

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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Research profile. Read more

Research profile

The Institute for Integrated Micro and Nano Systems (IMNS) brings together researchers from integrated-circuit design, system-on-chip design, image-sensor design, bioelectronics, micro/nano-fabrication, microelectromechanical systems (MEMS), micromachining, neural computation and reconfigurable and adaptive computing.

Research interests include low-level analogue, low-power, adaptive and bio-inspired approaches, system-on-chip computing and applications from telecommunications to finance and astronomy. There is also a research focus on integrating CMOS microelectronic technology with sensors and microsystems/MEMS to create smart sensor systems. We also have a strong and growing interest in applications relating to life sciences and medicine, with particular focus on bioelectronics, biophotonics and bio-MEMS.

IMNS has laboratory facilities that are unique within the UK, including an advanced silicon and MEMS micro-fabrication capability coupled with substantial design and test resources. The Institute has an excellent reputation for commercialising technology.

Training and support

The development of transferable skills is a vital part of postgraduate training and a vibrant, interdisciplinary training programme is offered to all research students by the University’s Institute for Academic Development (IAD). The programme concentrates on the professional development of postgraduates, providing courses directly linked to postgraduate study.

Courses run by the IAD are free and have been designed to be as flexible as possible so that you can tailor the content and timing to your own requirements.

Our researchers are strongly encouraged to present their research at conferences and in journal during the course of their PhD.

Every year, the Graduate School organises a Postgraduate Research Conference to showcase the research carried out by students across the Research Institutes

Our researchers are also encouraged and supported to attend transferable skills courses provided by organisations such as the Engineering and Physical Sciences Research Council (EPSRC).

Facilities

The Institute has laboratory facilities that are unique within the UK, including a comprehensive silicon and MEMS micro-fabrication capability coupled with substantial design and test resources.

The Institute has an excellent reputation for commercialising technology.

Research opportunities

We offer a comprehensive range of exciting research opportunities through a choice of postgraduate research degrees: MSc by Research, MPhil and PhD.

Masters by Research

An MSc by Research is based on a research project tailored to a candidate’s interests. It lasts one year full time or two years part time. The project can be a shorter alternative to an MPhil or PhD, or a precursor to either – including the option of an MSc project expanding into MPhil or doctorate work as it evolves. It can also be a mechanism for industry to collaborate with the School.



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The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. Read more

Research profile

The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.

We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.

Our research falls into three areas:

-machine learning
-computational neuroscience
-computational biology

In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.

In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments

The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).

Training and support

You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.

A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.

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

Facilities

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

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

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

Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

The research you will undertake at IANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.

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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. Read more

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

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