Masters Degrees (Brain Science)

Over the last two decades there has been an explosion of interest in brain science across academia, industry and the media. The integration of cognitive brain imaging with neuroscience will play a central part in discovering how the brain functions in health and disease in the 21st century, as illustrated by the Human Brain Project in Europe and The Brain Initiative in the USA. The taught Brain Sciences Degree will help you gain interdisciplinary knowledge “from molecules to mind” and enable you to develop research skills in cognitive brain imaging, fundamental neuroscience and brain disorders.

Why this programme

◾You will study the Brain Science Degree in an Institute that strives to understand the brain at multiple levels of function, from cells to cognition using approaches ranging from molecular, cellular and systems level investigations to brain imaging o
◾Lectures will be given by staff who are international research leaders and who publish cutting edge research at the forefront of brain sciences.
◾You will attend seminars on a wide range of topics given by eminent external speakers visiting the Institute from around the world as part of our Current Research Topics course.
◾You will carry out a research project working in labs equipped with technology and expertise at the forefront of brain science research, including: ◾3 Tesla fMRI system to image human brain function
◾Magnetoencephalography and electroencephalography to study neural activity
◾Transcranial magnetic stimulation for non-invasive brain stimulation
◾7 Tesla experimental MRI scanner for studying models of disease
◾Confocal microscopy for high resolution cellular imaging
◾Models of disease for pharmcolgical, gene and stem cell therapies

◾You will receive in depth training in research design and statistical analysis
◾The brain science programme allows student choice and flexibility. Through your choice of optional taught courses you can develop in-depth specialist knowledge to enhance further academic research as well as transferable skills for a career outside academia.
◾You will join a vibrant community of masters students from other programmes and for your research project you will be based in laboratories alongside PhD students, postdocs and senior researchers.
◾Through the range of teaching methods and assessments used you will gain skills in critical appraisal, independent working, presentations, writing scientific documents and time management.

Programme structure

The programme will consist of compulsory taught courses, selected optional courses and a research project spread over 11-12 months.

Core courses and Research Project

◾Fundamentals for neuroscience research
◾Cognitive brain imaging
◾Statistics and research design
◾Current research topics in brain sciences
◾Neuroscience: animal models of disease and function
◾Designing a research project
◾Brain sciences research project

Optional courses

◾Introduction to Matlab for biologists
◾Neuroscience: in vivo models
◾In vitro and analytical approaches in neuroscience
◾Bioimaging for life sciences
◾Current trends and challenges in biomedical research and health
◾Technology transfer and commercialisation of biomedical research
◾Neuroinflammation

Teaching and Learning Methods

Taught courses are delivered by lectures, tutorials, problem-based learning and computer-based sessions supplemented by a wide range of electronic resources for independent or group study. You will use the primary scientific literature as an information resource and through project work will develop skills in team-working, experimental design and data interpretation. Through assessment of coursework you will gain skills in oral and written communication.

Career prospects

The University of Glasgow MSc in Brain Sciences provides you with many career opportunities.

Research: MSc students can enter a research career, mainly by undertaking further postgraduate research studies towards a PhD, or by working in research laboratories in academic settings.

Industry: Other options include going on to work in a wide range of commercial sectors including the pharmaceutical or biotechnological industries and scientific publishing.

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This programme involves studying the interaction between and within groups of neurons in the brain, and how they affect our interactions with the outside world.

The brain is no longer considered a passive response device but rather as a network in which we consider ongoing activity before, during, and after a stimulus. The specialisation Brain Networks and Neuronal Communication deals with brain networks; ranging from the smallest scale, the communication between individual neurons, to the largest scale, communication between different brain areas. Using advanced mathematical tools, this specialisation prepares students for cutting-edge neuroscience research.
Students interested in this specialisation are expected to already have a high level of mathematical skills and/or training in physics, engineering or computer science in their Bachelor’s studies.

A large majority of our graduates gain a PhD position, while other graduates find jobs in the commercial sector or at research institutes. Graduates of this specialisation may more readily find a position within a government institution or specialised companies (e.g. in the pharmaceutical industry).

See the website http://www.ru.nl/masters/cns/brain

Why study Brain Networks and Neuronal Communication at Radboud University?

- Researchers in Nijmegen combine new techniques for electrophysiological and anatomical measurements of connectivity and activation with data analysis and the experimental application of these techniques. This is done in studies of cognition in not just humans but also non-human primates and rodents.
- Exceptional students who choose this specialisation have the opportunity to do a double degree programme with either Neuroscience or Artificial Intelligence. This will take three instead of two years.
- This competitive programme provides a sound balance of theory and practice. Our selective approach guarantees excellence, especially during the research training period.

Career prospects

If you have successfully completed the Master’s programme in Brain networks and neuronal communication, you will be able to conduct independent neuroimaging and neurobiological research. You will have ample knowledge of the anatomical and neurophysiological aspects of networks in the human brain and the techniques for the computational analysis and modeling of brain networks. This will enable you to conduct independent research into the neurofunctional architecture of key cognitive functions, such as perception, attention, memory, language, planning and targeted actions and develop technologies to measure, characterise and model networks at the whole brain and/or the local cortical circuit level. With this educational background you should be able to find a position with one of the research institutes in the Netherlands or abroad, government institutions or specialised companies (e.g. in the pharmaceutical industry).

Our approach to this field

Research in the field of cognitive neuroscience is one of the spearheads in the research policy of Radboud University. Here, in Nijmegen, hundreds of scientists from various faculties and top institutes have joined forces to unravel the workings of the human brain, step by step . They work together closely, exchange expertise and share state-of-the-art research equipment.

Nijmegen is one of the foremost centres of cognitive neuroscience in the world. We have a high admission threshold to ensure that all of our students are highly motivated and have the ability to work at an advanced level. Top scientists screen all applications to make sure the new students meet our stringent entry criteria and can maintain the current standards of excellence. Once admitted to the programme, you can expect to be trained as a multidisciplinary scientist in the following two years. The research you will undertake addresses crossdisciplinary challenges. The teachers and supervisors you will meet are all experts in their own disciplines. We hope that with this programme, you will outperform your teachers by being able to combine knowledge from different domains. Alongside language processing and perceptuomotor systems, you may also help improve brain/computer interfaces, a hot topic with applications in medicine and information technology. Apart from being very exciting, it is also logical that various disciplines are merging. After all, everything that happens in the brain is interconnected. In Nijmegen we develop sophisticated cognitive models which we test by means of state-of-the-art imaging techniques, thanks to which you can participate in cutting-edge research that will hopefully lead to new insights into the way the human brain and mind work. Finally, we offer our best CNS students excellent career opportunities in challenging PhD projects.

- Unique multi-disciplinary Master’s programme
Are you also interested in the human brain? Would you like to conduct research into the workings of the brain and join an enthusiastic, international group of top researchers? The Radboud University offers a multi-faculty Master’s programme in Cognitive Neuroscience. The programme takes two years and is of a scientific orientation. There is a strong emphasis on experimental research. This Master’s programme is unique in Europe.
The Master’s programme in Cognitive Neuroscience is primarily focused on training you as a researcher because research institutes and businesses around the world desperately need highly qualified and motivated young researchers. Moreover, since cognitive neuroscience is a rather young discipline, much in this field has not yet been explored. There are many challenging questions that need to be answered. So there is plenty of room for new discoveries!

This competitive programme provides a sound balance of theory and practice. We enrol about 50 students per year. Our selective approach guarantees excellence, especially during the research training period.

See the website http://www.ru.nl/masters/cns/brain

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Over the last decades, improvements in technology have led to a rapid increase in the use of neuroimaging to study human brain function non-invasively in health and disease. In particular, functional magnetic resonance imaging (fMRI), electro-encephalography (EEG), magneto-encephalography (MEG) and transcranial magnetic stimulation (TMS) are now routinely used by neuroscientists to study brain-behaviour relationships. Our MSc in Brain Imaging showcases Nottingham’s multi-disciplinary environment and offers a comprehensive programme that will provide you with the theoretical knowledge and practical skills required to conduct high-quality neuroimaging work and neuroscience research. Translational in vivo neuroscience approaches in animal models will also be considered, and interested students will have the opportunity to receive research training in this area.

The MSc in Brain Imaging has a flexible course structure and offers four pathways with core modules alongside a choice of optional modules that permits tailor-made study. The options are:

MSc Brain Imaging (Cognitive Neuroscience)
MSc Brain Imaging (Neuropsychology)
MSc Brain Imaging (Integrative Neuroscience)
MSc Brain Imaging (Developmental Science)

Graduating from the University of Nottingham opens up a wide range of career options. Many of our students use this programme as a preparation for PhD study or other advanced degree positions. Others opt for science-related jobs. Our graduates are highly regarded by employers in private and public sector organisations because of the solid academic foundation and transferable skills they gain during their degree course such as analytical evaluation, data management, statistical analysis as well as presentation and writing skills. In the past, graduates of this programme have taken-up career opportunities in university, hospital and industry settings.

Please email [email protected] for more information or visit the PG prospectus. Given the breadth of training available, the MSc is recommended to students with a background in psychology, neuroscience or a bioscience discipline as well as those with training in physics, engineering, mathematics, or computer sciences.

Upcoming Open Days: Wednesday 29 June and Wednesday 6 July (1.30-3 pm). Please contact us if you have specific questions about the programme. Phone: +44 (0)115 951 5361 or email: [email protected]

Key facts

• Programme delivered through lectures, practicals and research project resulting in a dissertation
• Core and optional modules according to specific pathways
• Four pathways with applications in Cognitive Neuroscience, Developmental Science, Neuropsychology, and Integrative Neuroscience
• Taught by active and internationally renowned research scientists
• Interdisciplinary approach with specialist lectures and/or project supervision by scientists from: the School of Psychology; Sir Peter Mansfield Magnetic Resonance Centre; Department of Academic Radiology

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This innovative course in the growing area of behavioural science and behavioural economics combines multidisciplinary expertise from the Departments of Economics, Psychology and Warwick Business School. Warwick is one of the strongest places in the world to study behavioural science (flagged for excellence in the 2014 Research Excellence Framework), and one of the few to offer a truly interdisciplinary research and teaching team.

During the course you’ll focus on behavioural, experimental and neuroeconomics, decision-making and the principles of cognition. Methods explored include mathematical modelling of choice, agent-based simulation, econometrics and process-tracing methods (e.g. eye-tracking and brain-imaging).

You’ll also undertake a project, giving you the opportunity to collaborate with a team of researchers on live research projects. Past projects have included analysis of big data sets (e.g. Facebook profiles to large UK/US panel studies), large online experiments with thousands of participants, field experiments on consumer and economic behaviour, and laboratory studies of groups using economic games.

Our graduates continue to PhD research, or to work in the public and private sectors, applying behavioural science to public policy and business.

Science Track

The Science Track is intended for those with an undergraduate degree in science, or another quantitative subject. Students take a module in Behavioural Microeconomics in Term 1, which introduces classic microeconomics and the relationship to the new behavioural approach.

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A flexible and interdisciplinary programme, which challenges you to use your specific knowledge to unravel the workings of the human brain.

Our brain contains many ingenious networks of millions of interconnected neurons. Together, they have a storage capacity and flexibility that far exceed modern supercomputers, or any artificial intelligent system. The Master’s specialisation in Neuroscience aims at unravelling the neuro-biological and neuro-computational mechanisms of this fascinating, complex system. We study the full spectrum from molecule to man, and from experiment to advanced theory and models.

The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.

Choose your own angle

Neuroscience at the Science Faculty ranges from biology to physics and mathematics, and will thus appeal to students from different Master’s programmes. The programme can be readily adapted to your individual academic background – whether that is in the field of Biology, Mathematics, Physics or Computing Science. Apart from fundamental knowledge of the brain, the Neuroscience specialisation also provides you with a general background in the principles of complex systems, and of intelligent behaviour of living and artificial systems.

Why study Neuroscience at Radboud University?

- Radboud University is the only university in the Netherlands that covers the complete research field of Neuroscience, from cognition to behaviour, and from sub-cellular processes, to single cell analysis and big data.
- The specialisation is closely connected to the world-renowned Donders Institute for Brain, Cognition and Behaviour (DI). You will get the chance to work with DI researchers during your internship, and build up a high profile network for your future career.
- The courses have a strong focus on research: they will cover the latest developments in brain research and technology, and train you the essential academic skills.
- You will work with students and researchers from different backgrounds in the natural sciences and become acquainted with a wide variety of research methods and scientific approaches.

Change perspective

The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.

Career prospects

Master’s specialisation in Neuroscience
The Master’s specialisation in Neuroscience gives you the chance to work at the Donders Institute for Brain, Cognition and Behaviour, and build up your own network of international renowned scientists who are working on the human brain: an excellent preparation for a future career in science. Neuroscience will also provide you with general skills that are required for any other job you aspire:
- the ability to structure complex problems
- excellent social skills for working in a multidisciplinary team
- extensive experience in presentations
- academic writing skills

Our approach to this field

At Radboud University, all branches of Neuroscience are accounted for, and strongly intertwined through the Donders Institute for Brain, Cognition and Behaviour (DI). This unique combination of expertises is a real advantage for Neuroscience students: it gives you absolute freedom to develop your knowledge in your field of interest and a high profile network for your future career.

- Science faculty
In this specialisation at the Science faculty, you will use your background in the natural sciences to unravel neurobiological processes. When completed, you will receive a Master’s degree in Medical Biology, Molecular Life Sciences, Physics & Astronomy or Science. For highly talented students it is possible to obtain a second Master’s degree at the selective Research Master’s in Cognitive Neuroscience of the DI, which has a more cognitive approach. This extra Master’s degree takes one additional year (60 EC) to complete.

- Themes
The Master’s specialisation in Neuroscience focuses on three of the four research themes of the Donders Institute for Brain, Cognition and Behaviour:

- Perception, Action and Control
Focus: Studying sensorimotor mechanisms, their cognitive and social components, their clinical implications, and their relevance for robotics.

Research: Researchers use theoretical analysis, psychophysical and behavioural studies, neurophysiological techniques, neuroimaging, clinical and pharmacological interventions, developmental and genetic approaches.

- Plasticity and Memory
Focus: The development and decay of the healthy and the maladaptive brain.

Research: Researchers in this field study the mechanistic underpinnings and behavioural consequences of long-term changes in neural structure and function. Genetic, molecular and cellular methods, animal models, as well as human neuroimaging and cognitive neuropsychology are used.

- Brain Networks and Neuronal Communication
Focus: Complex neural networks, ranging from the very smallest – communication between individual neurons – to the largest: communication between different brain areas and the outside world.

Research: The research groups combine the development of new techniques for measurements of connectivity and activation, with the experimental application of these techniques in studies of cognition in humans, non-human primates and rodents. Computational modelling is an important component.

- Custom approach
The specialisation programme depends on the Master’s programme that you will follow. In this way, it will perfectly fit to your current knowledge and practical skills. However, as all neuroscience research topics are interdisciplinary, you will become acquainted with other disciplines as well. This will help you to develop a common ground that is necessary to communicate in a multi-faceted (research) team.

See the website http://www.ru.nl/masters/medicalbiology/neuro

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What do Facebook, the financial system, Internet or the brain have in common?

"Everything is connected, all is network"
From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals.

Our MSc Network Science will provide a thorough grounding in the core principles of modelling and analysis of complex and networked systems, along with the principal analytical and numerical methodologies. This will open to students a host of career opportunities in systems and networks modelling industries, spanning the IT, financial, and biomedical sectors, that are now requiring such specialist knowledge and skills.

Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), finance (financial risk and systemic instability, financial networks, interbank cross-correlations), marketing and IT (social media, data analytics), public health (epidemic spreading models), or biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), to cite a few. This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students with a mathematical background who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.

Why study your MSc Network Science at Queen Mary?
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.

We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. The coalescence of both groups expertises has fostered the creation of this unique MSc.

More about our two schools

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research, teaching excellence and unrivalled links with business and the public sector. The School of Mathematical Sciences has a distinguished history on itself. We have been conducting pioneering mathematical research since the 1950s, and as one of the largest mathematical departments in the UK, with over 50 members of staff, the school can offer diverse postgraduate study opportunities across the field, from pure and applied mathematics, to finance and statistics. Along with the MSc in Network Science, our cohort of postgraduate students specialise in Mathematics and Statistics, Mathematical Finance and Financial Computing. We are one of the UK’s leading universities in the most recent national assessment of research quality, we were placed ninth in the UK (REF 2014) amongst multi-faculty universities. This means that the teaching on our postgraduate programmes is directly inspired by the world-leading research of our academics. Our staff includes international leaders in many areas of mathematical research, and the School is a hive of activity, providing a vibrant intellectual space for postgraduate study.

The School of Electronic Engineering and Computer Science is internationally recognised for their pioneering and ground-breaking research in several areas including machine learning and applied network analysis. This expertise uniquely complements the more theoretical knowledge offered by the School of Mathematical Sciences, providing a well balanced mix of theory and applications and offering a deep and robust programme that combines the foundations of the mathematics of networks with the latest cutting edge applications in real world problems.

Additionally, Queen Mary holds a university-level Bronze Award for the Athena SWAN Charter, which recognises and celebrates good employment practice for women working in mathematics, science, engineering and technology in higher education and research.

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This MRes is an innovative research-led programme which brings together expertise from across the Faculty of Brain Sciences and offers you the opportunity to work and train with leading researchers at one of the most highly regarded centres of excellence in brain science in the world.

Degree information

Students will gain an understanding of the human brain and its disorders from the molecular to systems level that will reflect the interdisciplinary breadth of cutting-edge research in brain sciences conducted at UCL. Students will gain theoretical and practical knowledge of core personal and professional skills that underpin excellence in research.

Students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), one optional module (15 credits) and an extensive empirical research project (120 credits).

Core modules
-Research Methods I
-Research Methods II
-Contemporary Topics in Brain Sciences Research

Optional modules - students choose one of the following 15-credit optional modules:
-Cellular and Molecular Mechanisms of Disease
-Introduction to the Brain and Imaging the Brain
-Structure and Measurement of the Human Brain
-Introduction to Cognitive Science
-Principles of Cognition
-Molecular Pharmacology
-Developmental Neurobiology
-Receptors and Synaptic Signalling

Dissertation/research project
All students undertake an independent research project which culminates in a dissertation in the form of a journal article and an oral examination.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, independent study, journal clubs, independent and collaborative problem-based tasks, practical demonstrations and classes, computational work, and a supervised empirical research project. Assessment is through online tasks, unseen written examinations, essays, oral presentations, research-based tasks and a primary research article.

Careers

This programme will prepare students for research careers in academia, industry or business, nationally or internationally. The first cohort of students on the Brain Sciences MRes will graduate after 2014, therefore no information on graduate destinations is currently available.

Employability
The programme provides a broad understanding of brain sciences. The aim is to give students the best chance of obtaining a place on a relevant PhD programme. In addition the programme includes taught elements that will enhance employability. Transferable skills include statistical training, communication skills, training in research ethics, research governance and in enterprise.

Why study this degree at UCL?

This comprehensive programme will provide core knowledge and skills, and ensure that prospective PhD candidates are thoroughly acquainted with the background as well as with the expanding scope of the field.

The unique curriculum will develop knowledge and insight into the broad and interdisciplinary scope of brain science through practical experience and exposure to contemporary topics in brain sciences research delivered through a series of innovative masterclasses led by internationally renowned researchers at UCL.

With an empirical research project encompassing two-thirds of the programme, quantitative and qualitative tools for research will be developed including core skills in the implementation, management and dissemination of research.

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Overview

- Aims
It is our aim to develop in our students the skills required to submit a satisfactory MPhil thesis at the end of their chosen duration (1 year full time or 2 years part time). In order to achieve this, a student will have acquired the essential skills required to design and conduct experiments (including applying for ethics approval where necessary), to analyse results, and to communicate these both in writing and orally. These skills will include those that can be transferred successfully to their choice of academic or other career.

- Support
The MPhil at the CBU is achieved by supervised research and is under the jurisdiction of the Degree Committee for the Faculty of Biology. The provision of supervision and teaching is overseen by the Graduate School of Life Sciences. Within the CBU, the internal Graduate Committee is responsible for all aspects of the running of the degrees. A suitable project falling within the interests of the supervisor, and sustainable within the limits imposed by the facilities available at the CBU, is agreed by both student and supervisor, and endorsed by the Graduate Committee. Each graduate student has a primary Supervisor, who will supervise the main body of their research, and an Advisor who acts as a supplementary source of advice and support. We also have two pastoral tutors who offer personal support and counselling throughout a student’s time at the Unit.

- Seminars
Students attend a variety of Unit Seminars given by distinguished scientists. They are able to draw from the CBU’s panels of research volunteers, both normal and clinical, and enjoy the benefits of superb computing facilities and support staff, including a Graphics/Multimedia Officer.

- The Cambridge Graduate Programme in Cognitive and Brain Sciences
CBU students are full members of the Cambridge Graduate Programme in Cognitive and Brain Sciences, which has been jointly established by the Unit and the Departments of Psychology and Psychiatry. This consists of a weekly series of theoretical seminars presented by senior researchers from the CBU and from the University. Lectures will be held on Mondays 4-5.30pm in the West Wing Seminar Room at the MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge, CB2 7EF (unless otherwise specified), or at the Psychology department on the Downing Site in Cambridge city centre. Seminars are held during Michaelmas and Lent terms only.
All public talks are publicised on the University talks website, which also contains an archive of older lectures. All scientists at the CBU are expected to attend the two public talk series, held on Wednesdays and Thursdays.

- Facilities and Linkages
The CBU has excellent facilities for experimental behavioural studies involving normal populations and patients with brain damage, as well as institutional links with Addenbrooke’s hospital giving access to various types of patient populations, including stroke and progressive neural degenerative diseases. There is a 3 Tesla MRI scanner on the premises, as well as MEG and EEG facilities. Through its partnership with the University of Cambridge Wolfson Brain Imaging Centre, the CBU has excellent access to PET and additional fMRI (3 Tesla) facilities. The CBU also offers state of the art computing facilities, supporting Unix, PC, and Mac platforms, and handling the large volumes of neuro-imaging data as well as extensive computational modelling. All students have their own networked desktop computer, with internet access through JANET.
The Unit’s close links with the University Department of Psychology and the Department of Psychiatry are strengthened through the Cambridge Graduate Programme in Cognitive and Brain Sciences, a joint programme of termly Seminars given by members of each Department and attended by all graduate students.
The CBU is also an active member of the wider neuroscience community in Cambridge, supported by the Cambridge Neuroscience network.

- Completion on time
For MPhil students a personalised training and research programme will be agreed during the early weeks of the degree.

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

Learning Outcomes

By the end of the programme, students will have:
• a comprehensive understanding of techniques, and a thorough knowledge of the literature, applicable to their own research;
• demonstrated originality in the application of knowledge, together with a practical

understanding of how research and enquiry are used to create and interpret knowledge in their field;
• shown abilities in the critical evaluation of current research and research techniques and methodologies;
• demonstrated some self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Continuing

There is no automatic progression from a CBU MPhil degree to a CBU PhD. MPhil students will need to apply to be considered for a PhD place alongside all other candidates.

Teaching

We offer a variety of theoretical and skills based training to support our wide range of topics and streams of research. A personalised training programme will be agreed for each incoming student in the first few weeks of the degree period. This will cover an agreed timetable of attendance at the various seminars, the research project planned, amd the formal review points throughout the degree.

- Feedback
Continuous assessment and supervision. Students can expect to receive an online feedback report each term.

Funding Opportunities

For eligible applicants, several MRC funded studentships are available, which pay the University Composition Fee, and a small but liveable stipend (currently £13,726 p.a.), however it should be noted that this money has never been allocated to an MPhil student as we always have excellent eligible PhD students whose funding takes priority. In reality a MPhil would almost certainly need to be self-funded or have external funding. Hence, independently funded applications are very welcome, and we will also always nominate successful applicants for the various Cambridge University scholarships available, depending on individual eligibility.

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

Find out how to apply here http://www.graduate.study.cam.ac.uk/courses/directory/blcbmpbsc/apply

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

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The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Data science is a growing and important field of study with a fast-growing number of jobs and opportunities within the private and public sector. The application of theory and methods to real-world problems and applications is at the core of data science, which aims especially to use and to exploit big data.

If you are interested in solving real-world problems, you like to develop skills to use smart devices efficiently, you want to use and to foster your understanding of mathematics, and you are interested and keen to use statistical techniques and methods to interpret data, MSc Data Science at Essex is for you. You study a balance of solid theory and practical application including:
-Computer science
-Programming
-Statistics
-Data analysis
-Probability

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

You also benefit from being taught in our School of Computer Science and Electronic Engineering, who are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of their research rated ‘world-leading’ or ‘internationally excellent’ (REF 2014).

The collaborative work between our departments has resulted in well-known research in areas including artificial intelligence, data analysis, data analytics, data mining, data science, machine learning and operations research.

Our expert staff

Our Department of Mathematical Sciences 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.

The academic staff in our School of Computer Science and Electronic Engineering are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist staff working on data analytics include Dr Paul Scott, who researches data mining, models of memory and attention, and artificial intelligence, and Professor Maria Fasli, who researches data exploration, analysis and modelling of complex, structured and unstructured data, big data, cognitive agents, and web search assistants.

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 have six laboratories that are exclusively for computer science and electronic engineering students
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-You have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
-We host regular events and seminars throughout the year
-Collaborate with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
-The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to our internationally outstanding data science environment

Your future

With a predicted shortage of data scientists, now is the time to future-proof your career. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course opens the door to almost any industry, from health, to government, to publishing.

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.

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

-Dissertation (optional)
-MSc Project and Dissertation (optional)
-Applied Statistics
-Machine Learning and Data Mining
-Modelling Experimental Data
-Text Analytics
-Artificial Neural Networks (optional)
-Bayesian Computational Statistics (optional)
-Big-Data for Computational Finance (optional)
-Combinatorial Optimisation (optional)
-High Performance Computing (optional)
-Natural Language Engineering (optional)
-Nonlinear Programming (optional)
-Professional Practice and Research Methodology (optional)
-Programming in Python (optional)
-Information Retrieval (optional)
-Data Science and Decision Making (optional)
-Research Methods (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)

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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.
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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This Masters in Research Methods of Psychological Science will provide you with both theoretical instruction and practical experience in the methods appropriate for scientific research in psychology.

Why this programme

-With a 95% overall student satisfaction in the National Student Survey 2015, the School of Psychology continues to meet student expectations combining both teaching excellence and a supportive learning environment.
-This MSc complies with requirements for the PhD research training programme of the Economic & Social Research Council (ESRC) and can either be the first year of a ‘1+3’ funding package or qualify you for future ‘+3’ funding.
-The University of Glasgow’s School of Psychology is consistently ranked amongst the top 10 in the UK and top 5 in Scotland, recently achieving 1st in Scotland and 2nd in the UK (Guardian University Guide 2015).
-You will benefit from innovative assessment, including portfolio of professional skills, peer review and writing up a research project in the format of a journal article.
-You will benefit from access to the resources of the University’s Centre for Cognitive Neuroimaging (CCNi), including a 3 Tesla fMRI scanner, MEG system, two TMS labs, and several EEG labs, including fMRI compatible systems. Dedicated motion capture suites record precise 3D body movements and facial animation sequences. Eye movements can be followed remotely using our SR Research EyeLink systems.
-The programme has excellent career prospects and a very good track record of previous graduates.

Programme structure

Modes of delivery of the MSc in Research Methods of Psychological Science include lectures, seminars and tutorials and lab work.

Core courses
-Introduction to Matlab programming
-Professional skills
-Research methods in cognitive science
-Statistics and research design
-Advanced qualitative methods
-Designing a research project
-Research project

Optional courses (one chosen)
-Cognitive brain imaging methods
-Computational neuroscience
-Formal models and quantitative methods*
-Psychology of language*
-Sleep and circadian timing*
-Visual perception and cognition*

*Each of these options will only run if the minimum number of students (>3) enrol.

You will also attend Scottish universities’ psychology postgraduate meetings, research seminars and journal clubs.

Research excellence

Research across the subject of Psychology attempts to advance our understanding of behaviour and the underlying mental processes and brain functions at multiple levels of analysis. This effort entails the integration of diverse approaches and paradigms from experimental psychology, cognitive science and the cognitive neurosciences.

We are committed to producing basic and applied research of the highest quality with a focus on three main areas:
-An interdisciplinary effort to advance the understanding of the complex relationship between the brain, cognition and behaviour. This brings together researchers with an interest in cognitive neuroscience, functional neuroimaging, neuropsychology and computational modelling. The Centre for Cognitive Neuroscience (CCNi) aims to develop new methods for understanding brain mechanisms, and to train interdisciplinary scientists in the use of those methods and techniques.
-The new science of social interactions, a science that blends behavioural, computational and neuroimaging techniques to investigate human social function, communication and cooperation. Our research examines a range of mechanisms that underlie social interaction: from gestures and expressive signals, from the face, voice and body to language-based communication. We have special interest in how such local interactions affect the dynamics and structure of larger scale social networks.
-Further research areas include sleep, language, visual perception, computational methods, memory, thought and social interaction.

Career prospects

As this programme complies with ESRC requirements, successful graduates from the programme are eligible for +3 ESRC PhD studentships. The majority of our graduates have obtained PhD funding or secured a research or teaching position. Others have opted for further professional training in specialised fields of psychology. Some graduates have used the qualification and skills to advance in their current employment.

Graduates of this programme have gone on to positions such as: Assistant Psychologist at NHS and PhD studentships at Glasgow University or other HEIs in UK or abroad.

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Programme description

This programme combines the scientific study of human cognition with the application of cognitive science to broader societal concerns.

Students focus on core methodologies and theories of cognitive science, but also explore the synergy between cognitive science and its applications. This unifies forms of scholarly activity that are often pursued independently.

You will develop the skills to embark on your own research project and will learn how to communicate research, so if you are interested in developing a research career or in working within science communication, this programme will provide an excellent foundation.

Students who have well-developed written and oral communication skills will be encouraged to take on placement projects for knowledge exchange. Other students may choose to pursue scientific research that has implications for the broader society but aimed primarily at an academic audience.

Completion of the programme would provide the foundations of a research doctoral training programme, or a career in applied research or in science writing for the general public or non-academic professionals.

Programme structure

This programme comprises two semesters of taught courses, followed by a dissertation.

The taught component consists of a number of courses that are based around lectures, tutorials or small group seminars, and are assessed by oral presentations, essay or exam.

Compulsory courses:

• Cognition, Culture and Context
• Human Cognition: Science and Application to Society
• Introduction to Statistics and Experimental Design
• Pragmatics of Linguistic Communication
• Psychological Research Skills
• Transferring Knowledge to Society

Option courses may include:

• Advanced topics in Mind, Language and Embodied Cognition
• Child Bilingualism: Language and Cognition
• Cognitive Ageing and Cognitive Epidemiology
• Concepts and Categorisation
• Disorders of Language Functions
• Human-Computer Interaction
• Maturational Constraints on Language Acquisition
• Origins and Evolution of Language
• Psycholinguistics
• Psychology of Language Learning
• Simulating Language
• Working Memory in the Healthy and the Damaged Brain

The dissertation work, based on original research, is completed under the supervision of a member of staff with related research interests.

Learning outcomes

The MSc in Cognition in Science and Society aims to:

• provide a basis for research in the core theories of cognition, language, and communication
• provide a broad grounding in the research methods of the sciences of human cognition
• prepare students to undertake advanced cross-disciplinary research
• facilitate students' ability to integrate relevant cross-disciplinary knowledge
• prepare students to examine problems of importance to society, and develop strategies for addressing them through appropriate methods in the laboratory or in an applied setting
• enhance students' ability to communicate scientific findings to both the general public as well to the professionals in the public and private sectors
• develop students' skills in knowledge transfer

Career opportunities

This programme is intended for those who wish to pursue advanced research in human cognition in science and society. It may also be useful for those who wish to work in science communication.

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What do Facebook, the financial system, Internet or the brain have in common?

All are connected in a network. From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals.

Our MSc in Network Science will provide a thorough grounding in the core principles of modelling and analysis of complex and networked systems, along with the principal analytical and numerical methodologies. This will open to students a host of career opportunities in systems and networks modelling industries, spanning the IT, financial, and biomedical sectors, that are now requiring such specialist knowledge and skills.

Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), public health (epidemic spreading models), marketing and IT (social media, data analytics) to cite a few. This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students whose undergraduate degree is in mathematics or a cognate discipline who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.

Why study your MSc Network Science at Queen Mary?
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.

We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. The coalescence of both groups expertises has fostered the creation of this unique MSc.

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This qualification explores some of contemporary science's most pressing issues and develops a wide range of skills associated with postgraduate study. The MSc includes taught modules and a compulsory final project module which gives you the opportunity to explore a topic in further depth, and undertake a substantial piece of independent research.

Key features of the course

•Flexible study routes to suit your professional needs and interests
•Options include Earth Science, Brain and Behavioural Science and Medicinal Chemistry
•Develops critical, analytical and research skills, boosting your career or preparing you for further studies at doctoral level.

This qualification is eligible for a Postgraduate Loan available from Student Finance England. For more information, see our fees and funding web page.

Modules

If you are new to postgraduate level study we recommend that you take Developing research skills in science (S825) as your first module. You should study the project module last.

To gain this qualification, you need 180 credits as follows:

120 credits of optional modules from List A:

List A: Optional modules

• Developing research skills in science (S825)
• Molecules in medicine (S807)
• Earth science: a systems approach (S808)
• Concept to clinic (S827)
• Introduction to mental health science (S826)
• Space science (S818)

Or 90 credits from List A plus 30 credits from List B:

List B: Optional modules

• Capacities for managing development (T878)
• Making environmental decisions (T891)
• Managing for sustainability (T867)
• Project management (M815)
• The critical researcher: educational technology in practice (H819)
• The networked practitioner (H818)

plus

The following 60 credit compulsory module:

• MSc project module (S810)

The modules quoted in this description are currently available for study. However, as we review the curriculum on a regular basis, the exact selection may change over time.

Credit transfer

If you’ve successfully completed some relevant postgraduate study elsewhere, you might be able to count it towards this qualification, reducing the number of modules you need to study. Please note that credit transfer is not available for the MSc project module (S810). You should apply for credit transfer as soon as possible, before you register for your first module. For more details and an application form, visit our Credit Transfer website.

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This course is for you if you need to improve your language skills and subject knowledge of computing before going on to a Masters course. You improve your English language fluency and academic vocabulary, develop your academic skills, and gain experience of western methods of teaching and learning so that you can progress onto a relevant Masters course in our School of Computer Science and Electronic Engineering.

At Essex, you can progress onto our MSc Advanced Computer Science, MSc Advanced Web Engineering, MSc Artificial Intelligence, MSc Big Data and Text Analysis, MSc Cloud Computing, MSc Embedded Systems, or MSc Intelligent Systems and Robotics.

Our International Academy offers some of the best routes for international students to enter higher education in the UK. Our innovative courses and programmes have proved very successful with international students and have also attracted UK students because of the distinctive learning environment we offer.

If you are an international student, you may find that the education system in the UK is slightly different from other countries and, sometimes, that the transition to the British system can be challenging. Our courses help you to settle in and adapt to life in the UK.

Alongside improving your academic English skills, you also develop your knowledge and skills in computer programming. Our School is a community of scholars leading the way in technological research and development. Today’s computer scientists are creative people who are focused and committed, yet restless and experimental.

Our School of Computer Science and Electronic Engineering is ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of our research rated ‘world-leading’ or ‘internationally excellent’ (REF 2014).

Our expert staff

Our original Department of Computer Science was founded by Professor Tony Brooker, who came to Essex from Manchester where he had worked with Alan Turing. Professor Brooker invented the compiler-compiler, one of the earliest applications of a formal understanding of the nature of programming languages.

In recent years our School of Computer Science and Electronic Engineering has attracted many highly active research staff and we are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist facilities

By studying within our International Academy, you will have access to all of the facilities that the University of Essex has to offer:
-We provide computer labs for internet research; classrooms with access to PowerPoint facilities for student presentations; AV facilities for teaching and access to web-based learning materials
-Our new Student Services Hub will support you and provide information for all your needs as a student
-Our social space is stocked with hot magazines and newspapers, and provides an informal setting to meet with your lecturers, tutors and friends

You can also take advantage of our world-class computer science facilities:
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)

We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors.

Example structure

-English for Academic Purposes
-Programming in Python
-Advanced English for Academic Purposes
-Information Retrieval
-Critical Reading and Seminar Skills
-Extended English for Academic Purposes Project
-Computer Security (optional)
-Databases and Information Retrieval (optional)
-ICT Systems Integration and Management (optional)
-Operating Systems (optional)
-Web Application Programming (optional)

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