Cognitive neuroscience relates cognitive and behavioural functions to the underlying brain systems. Computational neuroscience uses data to construct rigorous computational models of brain function. Put them together and these new disciplines are the key to explaining the relationship between brain and behaviour.
You’ll develop a broad and critical understanding of these two fields, along with an appreciation of different approaches to understanding brain function.
Your range of computational and analytical skills, and an ability to generate and test hypotheses, will give you an excellent foundation for further research.
The course takes students from both life sciences and the physical sciences and engineering. Appropriate training is given to ensure all students can master the required skills and complete the course successfully.
You’ll develop the skills and knowledge for all sorts of careers. Many of our graduates continue to PhD level. Others work as research associates and assistant psychologists for employers such as universities and the NHS. Throughout your course, you’ll have frequent reviews with your tutor to discuss your learning needs and objectives.
Our ongoing collaborative projects with hospitals, mental health care units, the police and prison service, and several leading firms in business and industry will show you how psychology can be applied in the real world.
You’ll also benefit from our research excellence. We don’t just focus on one or two specialisms – with active researchers in most areas of psychology, we are consistently one of the highest-ranked research departments in the UK.
Whatever your particular interest, we have the facilities for your research. Our research environment was rated amongst the best in the country in the last national assessment. We are exceptionally well resourced for research in Social and Health Psychology, Clinical Psychology and Developmental Psychology, with a dedicated suite of rooms for different participant groups.
To give you the right tools for your research, there is a fully equipped neuroscience unit with excellent facilities for brain imaging, neuroanatomy, electrophysiology, behavioural neuroscience and computational neuroscience. We have access to a small-bore MRI device and to the University’s MRI facility for human studies.
Please contact us for the latest funding opportunities.
Teaching is through lectures, seminars and laboratory classes.
Examinations at the end of semesters one and two, written coursework and an extensive empirical research project over the summer.
The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.
We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.
Our research falls into three areas:
In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.
In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments
The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).
You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.
A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
The research you will undertake at ANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.
This MSc course aims to integrate two active and rapidly developing fields, computational neuroscience and cognitive robotics, to generate innovative strategies and solutions for scientific problems and technological limitations.
From modelling human cognition to programming robots to act in their environment, this course crosses the boundary between several disciplines, including biology, neuroscience, psychology, and computer science.
The CNCR MSc course is highly interdisciplinary encompassing psychology, cognitive science, neuroscience, computational modelling, neuroimaging, robotics, and patient rehabilitation. The Course is designed for those who are interested in applying knowledge of neural systems, brain function, and modeling to research in human cognition, perception, sensory and motor systems as well as the design of bio-inspired and biologically plausible robotic systems. It has a strong research focus with hands-on modules and practical applications. The course is aimed at both students from psychology/neuroscience with a strong quantitative background and at students from computer science and physics that want to apply their knowledge to neuroscience.
Programme organisation
A significant part of the CNCR MSc Course involves being part of a research group and conducting an independent research project. For this, you will be assigned to a supervisor and supervise the research project. Your research project is written up as the masters dissertation and counts for one third of your degree. Exposure to a different research group is intended to broaden research experience and widen research skills repertoire.
The course is organised jointly through the Schools of Psychology, Computer Science, Sport, Exercise and Rehabilitation Sciences and Electronic, Electrical and Systems Engineering.
Your choice of course modules will be individualised and agreed between you and your supervisor. The goal is to develop your knowledge and skills to allow you to carry out your research project in Semester 3 while learning a wide range of neuroscience, computation, and experimental method topics. Several modules rely on Matlab programming skills for their practical exercises, which could be used also in the placement and project. Students that don't have a sufficient programming knowledge will be required to attend a programming course in Semester 1.
You will be taught to devise a research plan, and will read and comment on scientific articles. You will choose the topic for your research project with the help of a research proposal module. A year-long CNCR Foundations module allows you to participate in CNCR seminars, journal clubs, and lab activities to have sufficient knowledge to carry out the research project. This will expose you to cutting edge research and labs.
For more module information see the Modules section.
Projects
You can select from a range of research topics depending on your areas of interest, and there are a number of supervisors who can provide support. See some of the recent projects and placements undertaken by students on the programme.
See MSc CNCR frequently asked questions (PDF 88KB)
Material is delivered through lectures, workshops and hands-on training in cutting edge laboratories.
Some of the key features of this course and areas of focus for student learning include:
You will receive training in computational and research methods, and will gain an overview of current research in neuroscience and robotics. The programme will prepare you to go onto high quality PhD programmes, leading to work in a range of fields from advanced robotics to cognitive neuroscience.
Many of our students receive job offers before they graduate. Recent students have found employment working and training in an IT consultancy; software engineering at Google; and setting up startup companies to develop IT products inspired by human cognition.
Several of our students receive PhD offers before completing the course; one of our recent students will be studying for a PhD in computational neuroscience at University College Dublin with funding secured via a postgraduate award from the Irish Research Council. Others choose to stay at Birmingham for PhD study. The course gives you an opportunity to showcase your talent in the School of Psychology and the School of Computer Science, and to increase your chances of pursuing an academic career within the University of Birmingham.
This course provides specialist expertise in core neuroinformatics (such as computing and biology) focusing on the development of research skills. It equips you with the skills to contribute to biologically realistic simulations of neural activity and developments. These are rapidly becoming the key focus of neuroinformatics research.
Newcastle is among the pioneers of neuroinformatics in the UK and hosted the £4m EPSRC-funded CARMEN project for managing and processing electrophysiology data. We are currently involved in a £10m EPSRC/Wellcome Trust-funded project. This is on implantable devices for epilepsy patients. We use computer simulations to inform about the stimulation location and protocol.
As the amount of data in the neurosciences increases, new tools for data storage and management are needed. These tools include cloud computing and workflows, as well as better descriptions of neuroscience data. Available data can inform computer simulations of neural dynamics and development. Parallel computing and new algorithms are needed in order to run large-scale simulations. There is high demand within academia as well as within industry involving healthcare informatics, brain-inspired computing, and brain-inspired hardware architectures.
The course is designed for students who have a good degree in the biological sciences (including medicine) or the physical sciences (computer science, mathematics, physics, engineering).
You will gain foundational skills in bioinformatics together with specialist skills such as computing programming, mathematics and molecular biology with a significant focus on the development of research skills.
We provide a unique, multidisciplinary experience that is essential for understanding neuroinformatics. The course draws together the highly-rated teaching and research expertise of our Schools of Computing Science, Mathematics and Statistics, Biology, Cell and Molecular Biosciences and The Institute of Neuroscience. We also have strong links with the International Neuroinformatics Coordinating Facility (INCF).
Research is a large component of this course. The emphasis is on delivering the research training you will need in the future to effectively meet the demands of industry and academia. Newcastle's research in life sciences, computing and mathematics is internationally recognised.
The teaching staff are successful researchers in their field and publish regularly in highly-ranked systems neuroinformatics journals. Find out more about the neuroinformatics community at Newcastle University.
Graduates of this course may want to apply for PhD studies at the School of Computing Science. In the past, all graduates have continued their career as PhD students either at Newcastle University or elsewhere.
Our experienced and friendly staff are on hand to help you. You gain the experience of working in a team in an environment with the help, support and friendship of fellow students.
Your five month research project gives you real research experience in neuroinformatics. You will have the opportunity to work closely with a leading research team in the School and there are opportunities to work on industry lead projects. You will have one-to-one supervision from an experienced member of the faculty, supported with supervision from associated senior researchers and industry partners as required.
The project can be carried out:
-With a research group at Newcastle University
-With an industrial sponsor
-With a research institute
-At your place of work.
The course is based in the School of Computing Science and taught jointly with the School of Mathematics and Statistics and the School of Biology, and the institutes of Cell and Molecular Biosciences, Genetic Medicine and Neuroscience.
We cater for students with a range of backgrounds, including Life Sciences, Computing Science, Mathematics and Engineering. Half of the course is taught and the remainder is dedicated to a research project. Our course structure is highly flexible. You can tailor your degree to your own skills and interests.
Semester one contains modules to build the basic grounding in, and understanding of, neuroinformatics theory and applications, together with necessary computational and numeric understanding to undertake more specialist modules next semester. Training in mathematics and statistics is also provided. Some of these modules are examined in January at the end of semester one.
Semester two begins with two modules that focus heavily on introducing subject-specific research skills. These two modules run sequentially, in a short but intensive mode that allows you time to focus on a single topic in depth. In the first semester two module, you will focus on learning about modelling of biochemical systems - essential material for understanding neural systems at a molecular level. The second module is selected from a number of options. There are up to four modules to choose from, allowing you to tailor the research training component of your degree to your preferences.
We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.
The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.
You will have dedicated computing facilities in the School of Computing. You will have access to the latest tools for system analysis and development. For certain projects, special facilities for networking can be set up.
You will enjoy access to specialist IT facilities to support your studies and access to a Linux based website that you can customise with PHP hosting services.
This course is about the relationship between brain function and mechanisms that underpin behaviour.
Computational neuroscience uses data to construct models of brain function. Cognitive neuroscience and human imaging relate function to its underlying neural substrate.
The course includes a long research project which gives you the chance to carry out an in-depth imaging study. The computational and analytical skills you’ll learn are great preparation for a PhD.
The course takes students from both life sciences and the physical sciences and engineering. Appropriate training is given to ensure all students can master the required skills and complete the course successfully.
For the taught component of the course, students choose one of two options: either a pathway focused on mathematics, computational neuroscience and MR-physics or a pathway focused on ethics, clinical neurology, neuroradiology and neuroanatomy, which includes a practical human brain dissection course.
You’ll develop the skills and knowledge for all sorts of careers. Many of our graduates continue to PhD level. Others work as research associates and assistant psychologists for employers such as universities and the NHS. Throughout your course, you’ll have frequent reviews with your tutor to discuss your learning needs and objectives.
Our ongoing collaborative projects with hospitals, mental health care units, the police and prison service, and several leading firms in business and industry will show you how psychology can be applied in the real world.
You’ll also benefit from our research excellence. We don’t just focus on one or two specialisms – with active researchers in most areas of psychology, we are consistently one of the highest-ranked research departments in the UK.
Whatever your particular interest, we have the facilities for your research. Our research environment was rated amongst the best in the country in the last national assessment. We are exceptionally well resourced for research in Social and Health Psychology, Clinical Psychology and Developmental Psychology, with a dedicated suite of rooms for different participant groups.
To give you the right tools for your research, there is a fully equipped neuroscience unit with excellent facilities for brain imaging, neuroanatomy, electrophysiology, behavioural neuroscience and computational neuroscience. We have access to a small-bore MRI device and to the University’s MRI facility for human studies.
Please contact us for the latest funding opportunities.
PATHWAY 1
OR
PATHWAY 2
Teaching is through lectures, seminars and laboratory classes.
There are examinations at the end of semesters one and two, written coursework and an extensive empirical research project over the summer.
The course is designed to prepare you for a PhD, but your experience could land you a job in the private sector as a lab technician or a developer.
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.
Option modules
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.
A minimum of 30 credits is required for the degree, excluding bridge courses. The graduate curriculum consists of seven core courses and additional elective courses, with an optional thesis (six credits) or research project (three credits).
Required Courses
Electives
Select two of the following:
The MSc by Research in Integrative Neuroscience is a one-year, full-time research programme covering all levels of modern neuroscience, which makes it an ideal programme to prepare you for a PhD.
We include molecular, cellular, systems, regenerative, cognitive, clinical and computational neuroscience. We also allow you to choose your specialty right from the start, allowing you to shape your learning around your interests and career goals.
You start with a taught component in the first 12 weeks, and attend ‘themed weeks’ which run in parallel with elective from which you choose your optional courses. The Elective optional courses include:
The elective courses run during the first 12 weeks on two half days per week. These will give you a deeper insight into the concepts and methodology of a specific field of interest.
For your research you can choose available projects or contact principal investigators from more than 120 groups in the Edinburgh Neuroscience community to develop your own project, which can range from psychology to nanoscience.
Examples of completed projects are:
This programme is designed to help you in your research career. Over 90% of students on the MSc by Research in Integrative Neuroscience have positive next destinations, including PhD, research or clinical career paths.
The program of the two-year MSc is designed to offer a training in a specialized area of psychology and aims to be recognized as a high-level qualification for academic and professional purposes at international level.
The course units range within psychology, neurology and psychiatry and their clinical applications (in collaboration with the Departments of Neuroscience and Medicine).
The whole degree is strongly focused on laboratories - equipped with instruments such as TMS, tDCS, GEODESIC software – which allow our students’ theoretical learning to be integrated with the use of this technology to the purpose of enhancing their practical skills too.
Our aim is to offer our students a multilevel approach to their studies within an international perspective.
Each academic year consists of two semesters.
First semester: classes from October to January - Winter exam session: January to February
Second semester: classes from March to June - Summer exam session: June to July
Extra exam session: August to September
Course units
Laboratories
The MSc represents a great starting point to continue with PhD studies, particularly in Cognitive Science and Neuroscience. At the same time, our graduates will also be prepared to pursue a professional training and career in Clinical Neuropsychology or a related discipline. They will have various employment opportunities especially within the emerging fields of psychology. One example? Designing cognitive tests through neuroimaging, electrophysiology and brain stimulation.
The University of Padova, the Veneto Region and other organisations offer various scholarship schemes to support students. Below is a list of the funding opportunities that are most often used by international students in Padova.
You can find more information below and on our website here: http://www.unipd.it/en/studying-padova/funding-and-fees/scholarships
You can find more information on fee waivers here: http://www.unipd.it/en/fee-waivers
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.
The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.
Students undertake modules to the value of 180 credits.
The programme consists of two core modules (30 credits), four to six optional modules (60 to 90 credits), up to two elective modules (up to 30 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.
Core modules
Optional modules
Students must choose 15 credits from Group One Options. Of the remaining credits, students must choose a minimum of 30 and a maximum of 60 from Group Two, 15 credits from Group Three and a maximum of 30 credits from Electives.
Group One Options (15 credits)
Group Two Options (30 to 60 credits)
Group Three Options (15 credits)
Please note: the availability and delivery of optional modules may vary, depending on your selection.
A list of acceptable elective modules is available on the Departmental page.
Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.
Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.
Further information on modules and degree structure is available on the department website: Computational Statistics and Machine Learning MSc
There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include: finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.
Recent career destinations for this degree
Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.
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 Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.
Coupled with the internationally renowned Gatsby Computational Neuroscience and the Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.
The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.
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: Computer Science
96% 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 Educational Neuroscience MA/MSc will introduce students to the methods and findings from the emerging field of educational neuroscience. It will develop their understanding of key issues in educational neuroscience and the application of neuroscience to education, and provide the opportunity for them to undertake research in educational neuroscience.
This programme will develop students' understanding of research processes and give them the opportunity to be taught by staff with a wide range of expertise in psychology of education and developmental cognitive neuroscience. Students will also benefit from strong links with psychological expertise in other colleges of the University of London, especially Birkbeck, with whom this is a joint award.
Students undertake modules to the value of 210 credits.
The programme consists of five core modules (90 credits) - four taught at Birkbeck and one at UCL - two optional modules (60 credits) - taught at the IOE - and a dissertation (60 credits).
Core modules
* indicates modules taken at Birkbeck
Optional modules
Dissertation/report
All students undertake an independent research project which culminates in a 10,000-word dissertation.
Teaching and learning
This programme is delivered by face-to-face daytime or evening sessions and attendance may vary depending on your choice of optional modules. It is assessed by coursework assignments of up to 5,000 words and a 10,000-word dissertation.
Further information on modules and degree structure is available on the department website: Educational Neuroscience MA/MSc
Graduates of this programme are currently working across a broad range of areas. Some are working as research assistants, while others have jobs as teachers. Graduates can also be found working as PhD students.
Employability
Students gain experience of thinking critically about how to apply scientific theories and findings to educational practice, and how to build an evidence base for education. These are crucial skills that aid career development in both the science and the education sectors.
The Department of Psychology & Human Development brings together staff with research and teaching interests that encompass psychological approaches to learning, development and teaching from early childhood to adulthood.
The Centre for Educational Neuroscience (CEN) was formed in 2008 to promote applications of cognitive neuroscience within educational research, and build partnerships with professionals to translate findings into new practice. The CEN involves 30+ academic staff with expertise in developmental psychology, pedagogy and learning technologies (UCL Institute of Education), cognitive neuroscience and educational psychology (UCL) and developmental neuroscience and computational modeling (Birkbeck).
The CEN established the MA/MSc in Educational Neuroscience, with an intake of psychology graduates and education professionals, which feeds into an ESRC-accredited doctoral training pathway.
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: Psychology & Human Development
78% 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.
Our department is home to a world-renowned sensory neuroscience research group. Their projects provide the basis for teaching and research training on this MSc.
The course covers molecular, cell and developmental biology of auditory and visual systems. Advanced imaging and behavioral analysis focus on information processing: from sensory transduction to the central nervous system and behaviour. You’ll also study animal models of sensory deficits and the development of therapeutic treatments for hearing loss and blindness.
Graduates with skills in stem cell and regenerative medicine are in demand. Your degree will prepare you for a career in research in academia or industry, or in a clinical-related field. Our graduates are working all over the world – from the UK to China, India and the USA – and over half go on to doctoral study.
The 2014 Research Excellence Framework (REF) rates us No 1 in the UK for research in this field. Our international reputation attracts highly motivated staff and students. Sheffield is a vibrant place to take a masters based on pioneering research.
Regular seminars from distinguished international experts help you to connect your studies to the latest developments. We’re also part of collaborative research groups for developmental biology, cell biology, physiology, pharmacology, neuroscience, models of human disease, stem cell science and regenerative medicine.
Our three research centres focus on translating laboratory research to the clinical environment: Bateson Centre, the Centre for Stem Cell Biology, and the Centre for Membrane Interactions and Dynamics.
We have a long track record of groundbreaking discoveries. These include breakthroughs in human stem cells for hearing repair, and the generation of animal models for Parkinson’s disease, schizophrenia, muscular dystrophies and their use for therapeutic studies.
We have purpose-built facilities for drosophila, zebrafish, chick and mouse genetics and for molecular physiology. Other facilities provide all the tools you’ll need to examine and analyse a range of cellular structures. We have an electron and a light microscopy centre, a PCR robotics facility, a flow cytometry unit and an RNAi screening facility.
There are lectures, practical classes, tutorials and seminars. In small group teaching classes you’ll discuss, debate and present on scientific and ethical topics. Laboratory placements within the department provide you with one-to-one attention, training and support to do your individual research project. Assessment is by formal examinations, coursework assignments, debates, poster presentations and a dissertation.
Our teaching covers ethics, practical scientific skills and an overview of the current literature. You’ll also develop useful career skills such as presentation, communication and time management.
A flexible and interdisciplinary programme, which challenges you to use your specific knowledge to unravel the workings of the human brain.
Our brain contains many ingenious networks of millions of interconnected neurons. Together, they have a storage capacity and flexibility that far exceed modern supercomputers, or any artificial intelligent system. The Master’s specialisation in Neuroscience aims at unravelling the neuro-biological and neuro-computational mechanisms of this fascinating, complex system. We study the full spectrum from molecule to man, and from experiment to advanced theory and models.
The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.
Neuroscience at the Science Faculty ranges from biology to physics and mathematics, and will thus appeal to students from different Master’s programmes. The programme can be readily adapted to your individual academic background – whether that is in the field of Biology, Mathematics, Physics or Computing Science. Apart from fundamental knowledge of the brain, the Neuroscience specialisation also provides you with a general background in the principles of complex systems, and of intelligent behaviour of living and artificial systems.
- Radboud University is the only university in the Netherlands that covers the complete research field of Neuroscience, from cognition to behaviour, and from sub-cellular processes, to single cell analysis and big data.
- The specialisation is closely connected to the world-renowned Donders Institute for Brain, Cognition and Behaviour (DI). You will get the chance to work with DI researchers during your internship, and build up a high profile network for your future career.
- The courses have a strong focus on research: they will cover the latest developments in brain research and technology, and train you the essential academic skills.
- You will work with students and researchers from different backgrounds in the natural sciences and become acquainted with a wide variety of research methods and scientific approaches.
The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.
Master’s specialisation in Neuroscience
The Master’s specialisation in Neuroscience gives you the chance to work at the Donders Institute for Brain, Cognition and Behaviour, and build up your own network of international renowned scientists who are working on the human brain: an excellent preparation for a future career in science. Neuroscience will also provide you with general skills that are required for any other job you aspire:
- the ability to structure complex problems
- excellent social skills for working in a multidisciplinary team
- extensive experience in presentations
- academic writing skills
At Radboud University, all branches of Neuroscience are accounted for, and strongly intertwined through the Donders Institute for Brain, Cognition and Behaviour (DI). This unique combination of expertises is a real advantage for Neuroscience students: it gives you absolute freedom to develop your knowledge in your field of interest and a high profile network for your future career.
- Science faculty
In this specialisation at the Science faculty, you will use your background in the natural sciences to unravel neurobiological processes. When completed, you will receive a Master’s degree in Medical Biology, Molecular Life Sciences, Physics & Astronomy or Science. For highly talented students it is possible to obtain a second Master’s degree at the selective Research Master’s in Cognitive Neuroscience of the DI, which has a more cognitive approach. This extra Master’s degree takes one additional year (60 EC) to complete.
- Themes
The Master’s specialisation in Neuroscience focuses on three of the four research themes of the Donders Institute for Brain, Cognition and Behaviour:
- Perception, Action and Control
Focus: Studying sensorimotor mechanisms, their cognitive and social components, their clinical implications, and their relevance for robotics.
Research: Researchers use theoretical analysis, psychophysical and behavioural studies, neurophysiological techniques, neuroimaging, clinical and pharmacological interventions, developmental and genetic approaches.
- Plasticity and Memory
Focus: The development and decay of the healthy and the maladaptive brain.
Research: Researchers in this field study the mechanistic underpinnings and behavioural consequences of long-term changes in neural structure and function. Genetic, molecular and cellular methods, animal models, as well as human neuroimaging and cognitive neuropsychology are used.
- Brain Networks and Neuronal Communication
Focus: Complex neural networks, ranging from the very smallest – communication between individual neurons – to the largest: communication between different brain areas and the outside world.
Research: The research groups combine the development of new techniques for measurements of connectivity and activation, with the experimental application of these techniques in studies of cognition in humans, non-human primates and rodents. Computational modelling is an important component.
- Custom approach
The specialisation programme depends on the Master’s programme that you will follow. In this way, it will perfectly fit to your current knowledge and practical skills. However, as all neuroscience research topics are interdisciplinary, you will become acquainted with other disciplines as well. This will help you to develop a common ground that is necessary to communicate in a multi-faceted (research) team.
See the website http://www.ru.nl/masters/medicalbiology/neuro
The Bioinformatics MSc combines foundational skills in bioinformatics with specialist skills in computing programming, molecular biology and research methods. Our unique, interdisciplinary course draws together highly-rated teaching and research expertise from across the University, equipping you for a successful career in the bioinformatics industry or academia.
This interdisciplinary course is based in the School of Computing Science and taught jointly with the School of Biology, School of Mathematics and Statistics, Institute of Cell and Molecular Biosciences and the Institute of Genetic Medicine. It is designed for students from both biological science and computational backgrounds. Prior experience with computer programming is not required and we welcome applications from students with mathematical, engineering or other scientific backgrounds.
Our graduates have an excellent record of finding employment (around 90%). Recent examples have included:
-Bioinformatician at the Medical Research Council
-Technical consultant at Accenture
-Bioinformatics technician at Barcelona Supercomputing Centre.
Our course structure is highly flexible and you can tailor it to your own skills and interests. Half of the course is taught and the remainder is dedicated to a research project.
As research is a large component of this course, our emphasis is on delivering the research training you will need to meet the demands of industry and academia now and in the future. Our research in bioinformatics, life sciences, computing and mathematics is internationally recognised. We have an active research community, comprising several research groups and three research centres.
You will be taught by academics who are successful researchers in their field and publish regularly in highly-ranked bioinformatics journals. Our experienced and helpful staff will be happy to offer support with all aspects of your course from admissions to graduation and developing your career.
The course is part of a suite of related programmes that include:
-Synthetic Biology MSc
-Computational Neuroscience and Neuroinformatics MSc
-Computational Systems Biology MSc
All four courses share core modules. This creates a tight-knit cohort that has encouraged collaborations on projects undertaking interdisciplinary research.
Semester one combines bioinformatics theory and application with the computational and modelling skills necessary to undertake more specialist modules in semester two. We provide training in mathematics and statistics and, for those without a biological first degree, we will also provide molecular biology training. Some of these modules are examined in January at the end of semester one.
Semester two begins with two modules that focus heavily on introducing subject-specific research skills. These two modules run sequentially, in a short but intensive mode that allows you time to focus on a single topic in depth. In the first of the second semester modules you learn how to analyse data arising from post-genomic studies such as microarray analysis, proteomic analysis and RNAseq. All of the semester two modules are examined by in-course assessment - there are no formal examinations in these modules.
Your five month project gives you an opportunity to develop your knowledge and skills in depth, and to work in a research or development team. You will have one-to-one supervision from an experienced member of staff, supported with supervision from industry partners as required.
The project can be carried out:
-With a research group at Newcastle University
-With an industrial sponsor
-With a research institute
-At your place of work.
We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.
The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.
The Department of Automatic Control and Systems Engineering (ACSE) at the University of Sheffield
