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Masters Degrees (Cognitive Computing)

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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Cognitive Neuroscience at Swansea University. Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Cognitive Neuroscience at Swansea University.

The MSc in Cognitive Neuroscience focuses on three specialist areas: neuroimaging, electroencephalography (EEG) and brain stimulation. Students will have the opportunity to gain employment in a wide range of disciplines after studying the current research in the field supported by practical hands on training in data processing and analysis.

Key Features of MSc in Cognitive Neuroscience

Performance:

  • In The Research Excellence Framework (REF) 2014 we were one of only four psychology departments in the UK to achieve a 100% 4* rating (maximum score possible) for the reach and significance of its work. In REF 2014, 44% of our submission was graded as 4* (the highest possible grading). Based on this measure we are ranked 14th (out of 82) in the UK.
  • Our Psychology department is ranked 5th in the UK for Graduate Prospects by The Times and Sunday Times University League Tables 2018.

Teaching and Employability:

  • Teaching is carried out by highly-respected, research active, professionals conducting research across a range of cognitive neuroscience research areas and publishing in top international journals
  • Cognitive Neuroscience Students benefit from state-of-the-art technology with over twenty general purpose research rooms and numerous specialised testing facilities
  • Ability to offer international students mentoring throughout the course

Facilities 

  • Learning resources and facilities include: the brain stimulation lab, EEG suite, 3T MRI scanner, a computer room with updated preprocessing and analysis software. 

MSc in Cognitive Neuroscience is at the intersection of cognitive science, brain imaging, and clinical neuroscience.

It is considered one of the most significant areas of contemporary science and it is beginning to transform the understanding of both normal and damaged brain function.

The importance of cognitive neuroscience has been recognised by the Welsh Government which created the multi-centre Wales Institute of Cognitive Neuroscience, drawing together the psychology departments at Swansea, Cardiff and Bangor Universities.

A core aspect of the provision for MSc in Cognitive Neuroscience will also be collaboration with the Medical School at Swansea University.

Modules

Modules on the MSc in Cognitive Neuroscience may include:

  • Theoretical Issues in Cognitive Neuroscience
  • Practical Applications in Cognitive Neuroscience
  • Statistical Methods
  • Computing skills
  • Generic Research Skills
  • Special Research Skills
  • Research Project in Cognitive Neuroscience
  • Neuropsychology
  • Introduction to Research Programming
  • Psychology of Ageing

MSc in Cognitive Neuroscience Course Structure

The full-time masters degree for Cognitive Neuroscience is studied over one year.

The part-time degree in Cognitive Neuroscience, is studied over two years.

Sessions may be arranged occasionally on other days of the week (e.g. visiting clinician talks/workshops and employability sessions). 

The Cognitive Neuroscience course is taught through a variety of methods including: blended learning, lectures, discussions/debates, critical assessment of peer-reviewed articles, hands-on data preprocessing and analysis, training in writing research reports, creating conference posters and effective presentations.

Who should apply?

The MSc in Cognitive Neuroscience course is suitable for:

- anyone looking for a valuable academic foundation for future doctoral training

- anyone looking to demonstrate their employability across a range of disciplines within cognitive neuroscience and related fields, including psychology, computing, neuroscience, medicine and computer science

- UK and international psychology graduates seeking positions as researchers in psychology, cognitive neuroscience or related fields.

- psychology graduates aiming to secure a PhD by research in a psychology, cognitive neuroscience, or a related discipline

- graduates from other disciplines such as Biology, Neuroscience, and Medicine who wish to develop further skills related to psychology and cognitive neuroscience

Career Prospects

On completion of the Cognitive Neuroscience course students will have the opportunity to apply to any competitive PhD programme in cognitive neuroscience nationally and internationally.

The Cognitive Neuroscience course opens up a range of career options within cognitive neuroscience and related fields including psychology, computing, neurosciences, medicine and computer science, as research associates/officers, teachers, lecturers, the business sector and administration. 

Staff Expertise

Many of the College of Human and Health Sciences team are leaders in their specialist fields of research. They undertake novel and original research in a variety of areas, including clinical and health psychology, brain injury, sleep, cognition, neuroscience and developmental psychology.

Postgraduate Community

The College of Human and Health Sciences has a vibrant postgraduate community with students drawn from a variety of backgrounds and nationalities. The College is known for its friendly, welcoming and supportive environment, which combined with its extensive facilities, state-of-the-art technology and superb beachside location, helps to ensure that students benefit from an exceptional student experience.

In addition, Cognitive Neuroscience students have access to a wide range of excellent facilities and equipment for realistic workplace experiences.



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Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Read more

Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Computational cognitive neuroscience is a young and exciting discipline that tackles these long-standing research questions by integrating computer modelling with experimental research.

This Masters programme will foster a new generation of scientists who will be trained in both neuro-computational modelling as well as cognitive neuroscience. Its core topics include:

  • Creating computational/mathematical models of neurons, circuits and cognitive functions
  • The fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour)
  • Advanced data analysis and neuroimaging techniques

The programme is suitable for students from a variety of disciplines including - but not limited to - psychology, computing, neuroscience, engineering, biology, maths and physics. Students with no prior programming experience are welcome.

Graduates of this Masters will acquire a unique set of complementary skills that will make them extremely competitive in securing research or analyst positions in both academia and industry.

Why study this course?

  • This cutting-edge programme is at the forefront of a new, rapidly emerging field of research.
  • It is multidisciplinary, conveying the theory and practice of computational and cognitive neurosciences.
  • Graduates of this programme will gain a competitive edge in the job market over graduates of other, standard programmes in related fields.

Modules & structure

You will study the following core modules:

You will also undertake a 60 credit research project investigating an aspect of cognitive neuroscience using computational modelling, advanced data analysis methods, or a combination of these techniques. Culminating in a 10,000 word dissertation, the project will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2.

Option modules

You will choose one option from the following two modules:

  • Data Programming
  • Introduction to MATLAB

You will also choose one of the following 4 options:

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

Skills & careers

Graduates of this programme will have the following assets in their portfolio:

  • A sound understanding of brain mechanisms and structures underlying cognition and behaviour
  • Knowledge or experience of experimental cognitive neuroscience methods
  • Skills in statistical data analysis
  • Knowledge of theory and practice of biologically constrained neural models of human brain function
  • Computer programming skills.

Such a cross-disciplinary profile will make graduates of this Masters particularly competitive on the job market, especially when applying for positions that require complementary expertise and skills.

The course prepares students for employment in areas including cognitive neuroscience, IT consultancy, cognitive robotics, as well as large enterprises developing software systems inspired by human cognition (e.g., web-search engines, systems for natural language processing, information extraction, data mining and human-computer interaction).

The course is also ideal preparation for further study at PhD level.



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Who is it for?. This Masters is ideal for those who have an undergraduate degree in Psychology or a related discipline and would like to build more knowledge and skills highly valued both in academic research and the clinical professions. Read more

Who is it for?

This Masters is ideal for those who have an undergraduate degree in Psychology or a related discipline and would like to build more knowledge and skills highly valued both in academic research and the clinical professions. The MSc is an ideal platform from which to progress to PhD studies, particularly in Cognitive or Social Neuroscience. Students will also be well-equipped should they wish to undertake further professional training in Clinical Psychology, or a related discipline.

Objectives

This Masters degree bridges three research and clinical disciplines:

  • Cognitive Neuroscience (the study of human brain functions such as memory, perception and language)
  • Clinical Neuroscience (the understanding of neurological, psychological or psychiatric illness via their neural and cognitive antecedents)
  • and Social Neuroscience (the investigation of brain processes that help us communicate, feel, learn and interact with others).

The major aim of this programme is to provide you with a thorough grounding in the neuroscience that underpins human cognitive brain function, clinical, social and affective interaction, and neuropathology.

Teaching will comprise of seminars, lectures, computing and statistics classes, and supervision of an individual research project. Your learning experience during the programme will be enhanced by an invited speaker’s programme of external experts who work in Clinical, Social or Cognitive neuroscience.

Academic facilities

You will have access to all the facilities and laboratories in the Psychology Department. Check our labs facilities in the Cognitive Neuroscience Research Unit (CRNU)the Baby lab, the Autism Research Group (ARG), the Human Memory Research Group, etc. For a full list of facilities visit the Psychology Department.

Our members have experience with a wide range of neuroscientific techniques, including neuropsychological testing, psychophysics, electrophysiology, and neuroimaging methods.  We have particular strengths in the use of Electroencephalography (EEG)Transcranial magnetic stimulation (TMS) and Transcranial Electric Stimulation (a weak current applied to the scalp), in addition to measures of human behaviour (e.g. response times, response errors, and eye movements) and physiological measures (e.g. galvanic skin response and heart rate).

We test neurologically normal individuals, special populations (e.g. people with synesthesia) and people with expertise or acquired skills (e.g. dancers, musicians, athletes), as well as people with brain damage (e.g. neglect or split-brain patients), psychiatric diagnoses (e.g. schizophrenia), sensory deficits (e.g. visual and hearing impairments) and developmental disorders (e.g. dyslexia or autism).

Placements

We facilitate clinical internships through our specialist research Centre for Psychological Wellbeing and Neuroscience (CPWN) and with the local Mind centre.

Teaching and learning

Teaching will be comprised of lectures, seminars, group work and discussions, workshops and tutorials, reports, computing and statistics classes and the individual research dissertation.

You will undertake independent study, supported by the teaching and learning team, and will receive detailed feedback on your coursework. You will be provided with assessment and grade-related criteria which will outline your intended learning outcomes, along with the skills, knowledge and attitudes you are expected to demonstrate in order for you to complete an assessment successfully. You will also be assigned a personal tutor as your primary contact, who will advise you on academic matters and monitor your progress through the programme.

You will find a supportive vibrant research environment in the Department. The course is taught by academics, who are internationally recognised experts in their field with different backgrounds in clinical, social and cognitive neuroscience.

Check out what is going on in our laboratories and at the Center for Psychological Wellbeing and Neuroscience (CPWN).

Find our more about our work on our Facebook group.

Assessment

Your learning will be assessed through essays, examinations, oral presentations, research methods projects and interpretation of statistical analyses, formal research proposals and a dissertation.

Modules

The programme consists of eight taught modules worth 15 credits each with around 30-34 hours of face-to-face contact, supported by online resources and an empirical research project (worth 60 credits).

You will learn about the latest advances in clinical, social and cognitive neuroscience and develop an appreciation of the reciprocal nature of research and practice in these domains. For example how insights from functional neuroimaging inform our understanding of neurological disorders and how clinical observations inform neurocognitive modelling.

Career prospects

This course will provide you with knowledge and skills highly valued both in academic research and the clinical professions. The MSc is an ideal platform from which to progress to PhD studies, particularly in Cognitive or Social Neuroscience. You will also be well-equipped should you wish to undertake further professional training in Clinical Psychology, or a related discipline.

The knowledge and skills you will acquire in this programme are highly valuable, whether you choose to pursue further research or an applied occupation. They will enhance your employability prospects in a wide range of sectors including the pharmaceutical industry, neuromarketing, the computing industry, science and the media, science and the arts, business or education.



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Course content. We have designed this MSc course in consultation with industry partners. This has enabled us to understand their needs for Data Scientists, what skills will be required and on successful completion of this course individuals will be highly employable within businesses. Read more

Course content

We have designed this MSc course in consultation with industry partners.

This has enabled us to understand their needs for Data Scientists, what skills will be required and on successful completion of this course individuals will be highly employable within businesses.

Having this close understanding of what industry needs makes this course relatively unique and the very best suited to these looking for a career in the Data Sciences. 

The course will be of specific interest to :

  • A mathematics graduate wishing to use your skills in a vocational business based environment
  • A computer science graduate wishing to follow a vocational route
  • Individuals currently working in Business and looking to grow their career through gaining Data Science and Business Analytics skills

Six modules go to make up this MSc:

  • Data Science Foundation
  • Managing Data
  • Data Exploration and Analysis
  • Mathematics
  • Machine Learning & Cognitive Computing
  • Data Visualisation and Presentation

The 1 year full time MSc course will be stimulating and interactive, making use of lectures, self-learning, workshops and hands-on projects. 

You will be assigned a Personal Tutor from the start of your course who will work with you throughout your studies to help you achieve your academic best. 

The knowledge we provide you with in these areas will give you all of the essential know-how on methods, tools and techniques to deliver in your career as a Data Scientist.

We believe Data Science is very much an intellectual ‘contact sport’ and through this course we provide you with every opportunity to put your theoretical knowledge into practice.

The project work we have imbedded within the course has been chosen and developed based on real-world scenarios across a range of industry and government sectors and is specifically designed to:

  • Provide an essential link between your theoretical learning and real-world challenges
  • Create an environment where you decide the methods and tools best suited to the challenge based on what you have learnt
  • Recreate some of the challenges facing industry and Government today and those very similar to what you will encounter in the workplace as a Data Scientist
  • Be adaptable to reflect new methods / tools and scenarios in this fast developing discipline
  • Be able upon completion of the projects to reference your experience in working with such challenges

Our facilities

You will undertake your workshops in training rooms that are bang up-to-date with design features, touch screen electronic white boards and high speed wifi; housed across three stunning Georgian mansions.

All of our current students love the learning environment, the culture, camaraderie and the fact that tutors know them by name so they are more than just a ‘face in the crowd’. 

You will have access to the very best IT facilities in order to support your studies. These range from computer labs to access to cloud analytics from the leading providers.

We will use software from the academic programs of the major enterprise I.T. vendors such as IBM and Amazon as well as commonly used open source programs and frameworks. 

From September 2018, many of the teaching sessions will take place in the purpose-built Engineering and Digital Technology building in the Bognor Regis campus.

What's more, you have lots of other facilities on this dedicated university campus including latest books, journals and online data in a truly modern library, an IT centre, a student zone complete with Costa Coffee, a gym and much more.

Where this can take you

The course has been designed to provide you with a very practical understanding of the issues associated with sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations. 

On completion of your MSc studies and successful graduation, you will have very transferable skills and can choose to move directly in to the workplace perhaps in retail, banking, government or transport.

Indicative modules

  • Data Science Foundation (20 Credits)
  • Managing Data (20 Credits)
  • Data Exploration and Analysis (20 Credits)
  • Mathematics (20 Credits)
  • Machine Learning & Cognitive Computing (20 Credits)
  • Data Visualisation and Presentation (20 Credits)
  • Dissertation/Project (60 Credits)

Teaching and assessment

Our approach to supporting your learning, and how your learning is assessed, is designed to mirror the workplace environment. With this in mind, key features of our approach to learning and assessment include the following: 

  • We place a lot of emphasis on course work related activity.
  • Opportunities to work with organisations on current commercial/business problems and projects. These experiences are used to provide the basis for assessments that enable you to apply your learning within authentic commercial situations.


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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 Neural Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.

On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.

See the website http://www.ru.nl/english/education/masters/neural-computing/

Why study Neural Computing 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.

- 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.

- 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.

-Computational framework for counterfactual predictive processing

In a recent paper we introduced a computational framework, based on causal Bayesian networks, to computationally flesh out the predictive processing processing framework in neuroscience. In this project we want to extend this to so-called counterfactually rich generative models in predictive processing. Such models encode sensorimotor contingencies, that is, they represent 'what-if' relations between actions and sensory inputs. We aim to further operationalize this account using Pearl's intervention and counterfactual semantics. In this project you will combine formal computational modelling with conceptual analysis. 

- 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 and technical expertise . 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 or joined recent startups.

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

Instead of an extended research project (45 ec) you can also choose to do a smaller (30 ec) research project plus a 15 ec internship, giving you plenty of hands-on experience with AI. We encourage students to do this internship abroad.



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This specialist course focuses on artificial intelligence and knowledge engineering, as well as the development of computational and engineering models of complex cognitive and social behaviours. Read more

This specialist course focuses on artificial intelligence and knowledge engineering, as well as the development of computational and engineering models of complex cognitive and social behaviours.

This taught postgraduate course is aimed at students who may not have studied computing exclusively, but who have studied a considerable amount of computing already.

If you want to become a specialist in a particular area of computing, this course will provide a first crucial step towards that goal.

This specialism focuses on artificial intelligence and knowledge engineering, and the development of computational and engineering models of complex cognitive and social behaviours. Study areas include: cognitive robotics, complexity, complex systems, computational finance, computer networks, and distributed systems. We also offer specialisms in:

  • Computational Management
  • Machine Learning
  • Security and Reliability
  • Software Engineering
  • Visual Computing and Robotics

Each specialism has a flexible mix of breadth and depth, consisting of two or three compulsory modules as well as choices from a selection of core and optional modules.

Further information

For full information on this course, including how to apply, see: http://www.imperial.ac.uk/study/pg/computing/artificial-intelligence/

If you have any enquiries you can contact our team at:



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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.

About this degree

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
  • Neuroscience of emotion and decision-making
  • Evolution and Social Behaviour

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.

Further information on modules and degree structure is available on the department website: Cognitive and Decision Sciences MSc

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.

Recent career destinations for this degree

  • Change Management Consultant, HCL AXON
  • Project Research Officer, Government Office for Science
  • Research Assistant, Imperial College London / University of Oxford
  • PhD in Financial Computing
  • Assistant Policy Adviser, Cabinet Office Behavioural Insights Team

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.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

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

London is one of the global hotspots 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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Division of Psychology & Language Sciences

83% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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Research programme. The academic staff in the Applied Computing Department (ACD) are all engaged in research and publications. Read more

Research programme

The academic staff in the Applied Computing Department (ACD) are all engaged in research and publications. Considering its modest size, ACD has successfully attracted research funding from various sources in the UK and the EU, including industry, research councils, HEA and EU framework projects such as FP6. Furthermore, ACD has been working and collaborating with many European research institutions.

For the academic year 2012-2013, 2 DPhil and 6 MSc students (1 in Mathematics) have graduated, four of whom graduated with Distinction. The 2 DPhil students have made it for the March graduation and we expect to have 3 or 4 more completing their DPhil research programmes for the next graduation. One of our new MPhil/DPhil students in Computing joined the Department last October, and 3 other MPhil/DPhil students have joined us since. Over the last few years, the number of research students in ACD has grown steadily to (currently) 29 PhD and 2 Master’s research students.

We have had over 20 refereed conference and journal papers published during the last 12 months, and two of the papers have been awarded best paper awards.

ACD supports diverse research topics addressing varied applied computing technologies such as:

  • Image processing and pattern recognition with applications in biometric-based person identification, image super-resolution, digital watermarking and steganography, content-based image / video indexing and retrieval, biomedical image analysis.
  • Multi-factor authentication and security algorithms.
  • Wireless networks technologies (Multi-frequency Software-Defined / Cognitive Radios, convergence and integration of different wireless technologies and standards such as WiFi and WiMax, IPv4 and IPv6, wireless mesh technologies, intrusion detection and prevention, efficiency and stability of ad hoc networks).
  • Hybrid navigation and localisation integrations for mobile handsets, including using Cellular and WiFi in conjunction with GPS and Glonass for seamless positioning indoors, Multiplexed receive chain of GPS/Glonass with on-board handset Bluetooth/WiFi, GNSS signals multiplexing for real time simulation.
  • Cloud computing, including the readiness of mobile operating systems for cloud services and focusing on techniques for fast computing handovers, efficient virtualisation and optimised security algorithms.
  • Data mining techniques, including database systems, the application of data mining techniques in image and biological data, human-computer interaction and visual languages.
  • Research and development of Apps for mobile devices and smart TVs, particularly for application in the areas of education and healthcare.
  • Differential geometry – Einstein metrics, quasi-Einstein metrics, Ricci solitons, numerical methods in differential geometry.

As well as researching the chosen subject, our students engage in delivering seminars weekly, attending conferences and workshops, attending online webinars and discussion forums, attending training and focused group studies, supervising tutorial and laboratory sessions for undergraduate students, peer reviews and final year project supervision, among a host of technical and networking activities to enhance their skills and techniques.

Find out more about our Department of Applied Computing on http://www.buckingham.ac.uk/appliedcomputing.

Apply here http://www.buckingham.ac.uk/sciences/msc/computingresearch.



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This highly practical course will appeal to computing graduates seeking careers as professional software engineers and equip them with the skills necessary to succeed. Read more
This highly practical course will appeal to computing graduates seeking careers as professional software engineers and equip them with the skills necessary to succeed.

Employers often complain that computing graduates lack real-world practical skills. The Advanced Software Development MSc addresses software development for new and emerging platforms such as mobile phones/pads, multi-core processors and cloud computing. Modern development environments, languages and tools are also covered.

All taught Master’s programmes at the School of Computing are available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/251/advanced-software-development

About the School of Computing

Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.

In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industrial Fellowships.

As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.

This programme is available with an optional industrial placement.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

CO838 - Internet of Things and Mobile Devices (15 credits)
CO846 - Cloud Computing (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO880 - Project and Dissertation (60 credits)
CO885 - Project Research (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO894 - Development Frameworks (15 credits)
CO889 - C++ Programming (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO641 - Computer Graphics and Animation (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO847 - Green Computing (15 credits)
CO899 - System Security (15 credits)

Assessment

Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation, except for the MSc in IT Consultancy for which the practical consultancy work is assessed through a series of reports covering each of the projects undertaken.

Programme aims

This programme aims to:

- enhance the career prospects of graduates seeking employment in the computing/IT sector

- prepare you for research and/or professional practice at the forefront of the discipline

- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)

- develop a variety of advanced intellectual and transferable skills

- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Careers

Students can gain practical work experience as part of their degree through our industrial placements scheme and KITC (see above). Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market. Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The Advanced Computer Science (Computational Intelligence) MSc programme combines a wide choice of advanced topics in computer science with specialist modules relating to computational intelligence, including logic-based, connectionist and evolutionary artificial intelligence, inspirations from the natural world, practical applications and the philosophy of machine reasoning. Read more
The Advanced Computer Science (Computational Intelligence) MSc programme combines a wide choice of advanced topics in computer science with specialist modules relating to computational intelligence, including logic-based, connectionist and evolutionary artificial intelligence, inspirations from the natural world, practical applications and the philosophy of machine reasoning.

While studying a taught Master’s programme at the School of Computing, you can gain work experience through our industrial placement scheme or with the Kent IT Consultancy (KITC), which provides a project-based consultancy service to businesses in the region. We have strong links with industry including Cisco, IBM, Microsoft and Oracle and are among the top ten in the UK for graduate employment prospects.

The programme is aimed at graduates considering a career in research and development. It would also provide an excellent foundation for PhD study.

This programme is available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/249/advanced-computer-science-computational-intelligence

About the School of Computing

Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.

In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industrial Fellowships.

As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

CO885 - Project Research (15 credits)
CO880 - Project and Dissertation (60 credits)
CO881 - Object-Oriented Programming (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO884 - Logic and Logic Programming (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO846 - Cloud Computing (15 credits)
CO847 - Green Computing (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO545 - Functional and Concurrent Programming (15 credits)
CO641 - Computer Graphics and Animation (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO834 - Trust, Security and Privacy Management (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO889 - C++ Programming (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
CO894 - Development Frameworks (15 credits)
CO899 - System Security (15 credits)
PL583 - Philosophy of Cognitive Science and Artificial Intelligence (30 credits)

Assessment

Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation, except for the MSc in IT Consultancy for which the practical consultancy work is assessed through a series of reports covering each of the projects undertaken.

Programme aims

This programme aims to:

- enhance the career prospects of graduates seeking employment in the computing/IT sector

- prepare you for research and/or professional practice at the forefront of the discipline

- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)

- develop a variety of advanced intellectual and transferable skills

- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Careers

Students can gain practical work experience as part of their degree through our industrial placements scheme and Kent IT Consultancy. Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market.

Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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This flexible course offers a largely free choice of modules from our range of Advanced Master's programmes. It is likely to appeal to computing graduates whose interests span more than one specialism and/or those seeking the freedom to explore a variety of advanced topics. Read more
This flexible course offers a largely free choice of modules from our range of Advanced Master's programmes.

It is likely to appeal to computing graduates whose interests span more than one specialism and/or those seeking the freedom to explore a variety of advanced topics. Depending on the options chosen, this course can serve as a springboard for employment or research.

This programme is available with an optional industrial placement. The course duration varies depending on the options taken.

Visit the website https://www.kent.ac.uk/courses/postgraduate/246/advanced-computer-science

About the School of Computing

Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.

In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industry Fellowships.

As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

CO880 - Project and Dissertation (60 credits)
CO885 - Project Research (15 credits)
CO881 - Object-Oriented Programming (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO846 - Cloud Computing (15 credits)
CO882 - Advanced Object-Oriented Programming (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO889 - C++ Programming (15 credits)
CO894 - Development Frameworks (15 credits)
CO899 - System Security (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO545 - Functional and Concurrent Programming (15 credits)
CO641 - Computer Graphics and Animation (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO834 - Trust, Security and Privacy Management (15 credits)
CO884 - Logic and Logic Programming (15 credits)
CO847 - Green Computing (15 credits)

Assessment

Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation.

Programme aims

This programme aims to:

- enhance the career prospects of graduates seeking employment in the computing/IT sector

- prepare you for research and/or professional practice at the forefront of the discipline

- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)

- develop a variety of advanced intellectual and transferable skills

- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Careers

Students can gain practical work experience as part of their degree through our industrial placements scheme and KITC (see above). Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market. Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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Computer security remains a hot topic in the media and there is strong demand for graduates with technical skills in this area. The programme addresses computer and information security holistically because vulnerability in any one component can compromise an entire system. Read more
Computer security remains a hot topic in the media and there is strong demand for graduates with technical skills in this area. The programme addresses computer and information security holistically because vulnerability in any one component can compromise an entire system.

This includes computer architectures, operating systems, network technologies, data storage and software development processes. A wide range of threats and other security issues (for example, denial-of-service attacks, hacking, viruses and worms) are covered along with defences and countermeasures.

The programme is aimed at computing graduates who are seeking careers as computer security professionals or who are interested in research. All taught Master’s programmes at Canterbury are available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/254/computer-security

About the School of Computing

Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.

In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industrial Fellowships.

As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

CO834 - Trust, Security and Privacy Management (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO880 - Project and Dissertation (60 credits)
CO885 - Project Research (15 credits)
CO899 - System Security (15 credits)
CO894 - Development Frameworks (15 credits)
CO889 - C++ Programming (15 credits)
CO846 - Cloud Computing (15 credits)
CO882 - Advanced Object-Oriented Programming (15 credits)
CO883 - Systems Architecture (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO545 - Functional and Concurrent Programming (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO847 - Green Computing (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
EL846 - Industrial Context of Biometrics (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO881 - Object-Oriented Programming (15 credits)

Assessment

Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation.

Programme aims

This programme aims to:

- enhance the career prospects of graduates seeking employment in the computing/IT sector

- prepare you for research and/or professional practice at the forefront of the discipline

- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)

- develop a variety of advanced intellectual and transferable skills

- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Careers

Students can gain practical work experience as part of their degree through our industrial placements scheme and KITC (see above). Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market. Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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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. Read more

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 three 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)

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 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.

Key facts

• Programme delivered through lectures, practicals and research project resulting in a dissertation

• Core and optional modules according to specific pathways

• Three pathways with applications in Cognitive Neuroscience, 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

Video

Watch our video of staff and students talking about the course.



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The MSc in Psychology of the Arts, Neuroaesthetics and Creativity is the first postgraduate programme in the world for the scientific study of aesthetics and creativity. Read more

The MSc in Psychology of the Arts, Neuroaesthetics and Creativity is the first postgraduate programme in the world for the scientific study of aesthetics and creativity.

At the intersection of the arts and the sciences, the programme introduces you to the psychology and the cognitive neuroscience of how humans generate new ideas, how we appreciate beauty, and how we form preferences.

Aesthetic and creative decisions are relevant in the visual and the performing arts, and in many applied and commercial contexts, ranging from clinical interventions to curating exhibitions, from dance choreography to marketing and advertising. Based in the Department of Psychology, in collaboration with Computing, Media and Communications and the Institute of Management Studies, the course builds critical knowledge, research and communication skills across the arts and the sciences, centred around two key topics: the psychological and brain mechanisms of making (Creativitiy) and appreciating (Neuroaesthetics) art. Conducting a research project with an interdisciplinary focus will prepare you for a research career in aesthetic or creative science, working in the creative industry, or to develop your artistic practice.

Goldsmiths is uniquely placed to offer this programme, with an internationally renowned reputation in the arts and the sciences. Existing courses combining art and psychology often have a largely therapeutic focus and rarely cover the psychology of aesthetic appreciation or creative cognition, in a broader profile. In contrast, business-oriented courses in marketing, advertising and consumer psychology often lack adequate scientific training in experimental psychology or cognitive neuroscience methods, which is required for a scientific approach to aesthetics and creativity. Optional modules based in the departments Media & Communications, Computing, and the Institute of Management Studies will complement and challenge the scientific perspective, acknowledging the richly diverse, unique and culturally-specific nature of human aesthetic and creative practice.

Modules & structure

On this programme you will study the following modules:

Neuroaesthetics (15 Credits): This module provides an in-depth introduction into the cognitive neuroscience of art appreciation, aesthetic perception and judgement from a basic science and an applied perspective. Topics include: psychological theories of aesthetic appreciation, aesthetic evolution, brain mechanisms of pleasure and reward, face and body attractiveness, and aesthetic science across the visual and performing arts, in laboratory and real-world settings.

Creativity (15 credits): This module provides a comprehensive introduction to the science of creative cognition. Adopting a multidisciplinary approach, this module covers latest research findings from various disciplines within cognitive psychology, social psychology, comparative and developmental psychology, creative arts and media, and neuroscience

Foundations of Neuroscience (15 credits): This module covers brain anatomy and function as well as an introduction to the available techniques to study the neural basis of behaviour. Topics range from single neuron architecture to the functional organization of brain systems. Neuroimaging methods covered include: fMRI, EEG, MEG and TMS.

Statistical Methods and Experimental Design (30 credits): This module covers experimental design and the theory and practice of quantitative data analysis. You will cover statistical techniques in the lectures, and learn to implement these techniques using statistical software in computer-based tutorials and workshops.

Research Skills/ Invited Speaker Series (15 credits): This module covers fundamental research skills: seminars on bibliographic searching, essay writing, research report writing, oral presentation skills, career planning and lab sessions. The second strand exposes students to cutting edge research in the field of aesthetic and creative cognition by means of an invited speaker series from a variety of academic disciplines, the creative industry and arts organizations. This module will be shared with students on the MSc in Music, Mind and Brain.

Research Project with an interdisciplinary focus (60 credits): You will conduct a quantitative research project in relation to aesthetics or creativity. The course encourages interdisciplinary and collaborative projects with other departments at Goldsmiths, or with external partners such as arts organizations or the creative industry.

Optional Modules (2 x 15 credits): You will choose two optional modules from within the Psychology Department (Advanced Quantitative Methods, Magic and the Mind) or collaborating Departments including Computing (Physical Computing and Workshops in Creative Coding), Media and Communications (Embodiment and Experience, Politics of the Audio-visual) and the Institute of Management Studies (Psychology of Marketing and Advertising, Consumer Behaviour). Optional modules will complement the scientific perspective with alternative views, approaches and extend your knowledge and skill base.

Please note that not all modules will be available and may change subject to approval



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This programme aims to prepare students for a successful career in the IT sector, even if they do not have a prior degree in computer science. Read more

This programme aims to prepare students for a successful career in the IT sector, even if they do not have a prior degree in computer science. It enables students who have studied computer science previously to expand their knowledge and acquire further skills across a broader range of computer science topics.

Taught modules address mobile and cloud computing, big data and database systems, and the importance of information security, in relation to the foundational information systems principles.

This programme will equip you with professional skills that will allow you to work as an IT consultant/manager, system architect/analyst, or software developer in any industry field that heavily relies on software and information technology.

Programme structure

This programme is studied full-time over one academic year and part-time over three academic years. It consists of eight taught modules and a dissertation.

Example module listing

The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.

Educational aims of the programme

The aims of the programme are to:

  • Prepare students for a range of computing related careers
  • Enable students to understand, design and apply information systems and software development technologies
  • Enable students to develop interest and basic skills for doing research in computer science
  • Enable students to realise their full potential for learning and communication
  • Enable students to appreciate rapid innovation and creativity in computer science

Programme learning outcomes

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

Knowledge and understanding

Students will gain an understanding of:

  • The principles of information systems and software development
  • The principles and applications of contents technologies
  • The practice of information systems and software development
  • The professional issues involved in the exploitation of computing
  • The areas of emergent and innovative computing technologies
  • The key research issues in information and software systems

Intellectual / cognitive skills

Students will be able to:

  • Understand and articulate the requirements of the users of software systems / applications
  • Succinctly present, to a range of audience, knowledge relevant to the building, testing and deployment of a system
  • Research and develop solutions through the application of systems analysis / software engineering methods

Professional practical skills

Students will gain the ability to:

  • Specify, design and develop software systems and applications
  • Critically evaluate software systems and tools
  • Work as a member of a development team
  • Communicate with potential and actual users and to understand their needs
  • Retrieve Information
  • Analyse data and present information in appropriate ways
  • Plan, research, manage and implement a major project

Key / transferable skills

Students will gain skills in:

  • Research and information retrieval skills
  • Numeracy in both understanding and presenting cases involving a quantitative dimension
  • Time management and organisational skills
  • Self-learning skills
  • Effective use of specialist IT facilities
  • Continuing professional development

Global opportunities

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.



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