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.
Teaching and Employability:
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 on the MSc in Cognitive Neuroscience may include:
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.
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
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.
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.
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.
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:
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.
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.
You will choose one option from the following two modules:
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.
Graduates of this programme will have the following assets in their portfolio:
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.
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.
This Masters degree bridges three research and clinical disciplines:
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.
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).
We facilitate clinical internships through our specialist research Centre for Psychological Wellbeing and Neuroscience (CPWN) and with the local Mind centre.
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.
Your learning will be assessed through essays, examinations, oral presentations, research methods projects and interpretation of statistical analyses, formal research proposals and a dissertation.
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.
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.
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 :
Six modules go to make up this MSc:
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:
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.
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.
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:
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.
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.
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.
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
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.
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:
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.
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: [email protected]
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.
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).
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
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
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.
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.
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.
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:
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.
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 [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.
• 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
Watch our video of staff and students talking about the course.
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.
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
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.
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.
The aims of the programme are to:
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:
Intellectual / cognitive skills
Students will be able to:
Professional practical skills
Students will gain the ability to:
Key / transferable skills
Students will gain skills in:
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.