PhD Programme

Training in theoretical and computational neuroscience and machine learning.

The Gatsby Unit is a centre for theoretical neuroscience and machine learning, focusing on unsupervised, semi-supervised and reinforcement learning, neural dynamics, population coding, Bayesian and nonparametric statistics, kernel methods and applications of these to the analysis of perceptual processing, neural data, natural language processing, machine vision and bioinformatics. It provides a unique opportunity for a critical mass of theoreticians to interact closely with each other, and with other world-class research groups in related departments at UCL, including Anatomy, Computer Science, Functional Imaging, Physics, Physiology, Psychology, Neurology, Ophthalmology, and Statistical Science, with the cross-faculty Centre for Computational Statistics and Machine Learning, the forthcoming Sainsbury Wellcome Centre for Neural Circuits and Behaviour and also with other UK and overseas universities notably, at the present time, with Cambridge in the UK, Columbia, New York and the Max Planck Institute in Germany.

Students at the Gatsby Unit study toward a PhD in either theoretical neuroscience or machine learning, with minor emphasis in the complementary field. Collaborative projects, for example with an experimental neuroscience group at UCL or elsewhere, are welcome, although the primary project supervisor should be one of the Gatsby (or Adjunct) faculty. Exceptionally, some students with pre-secured shorter-term studentships have joined us to study for an MPhil degree in one of these fields. Besides these Gatsby-funded programmes, students from some other PhD programmes are also able to carry out all or part of their research in Unit. See the links below. We do not offer undergraduate or taught masters programmes, nor (usually) a research masters. Again, links to alternative programmes appear below.

Structure		The PhD programme lasts four years, including a first year of intensive instruction in techniques and research in theoretical neuroscience and machine learning. In their first term, all students take the core courses in theoretical neuroscience and machine learning, after which they generally choose to concentrate on one of these fields. Each discipline runs a specialized course over the remainder of the first year, whilst the students start their research projects. In their second year, the students sit a written breadth exam in their chosen field, and write a shorter paper (equivalent to a short research proposal). The exam must be completed by the end of January of the second year, and the paper is due by August of the second year. Shortly afterwards, students are required to present and defend their thesis proposals in a talk given to the faculty. These must be held no later than June / July of the 2nd year. Having passed all the assessments, students then transfer from MPhil to PhD and are devoted to research for their remaining tenure. Failure to pass assessments by the deadlines outlined above will result in students having to meet with the entire faculty to explain their reasons for this. The faculty will consider whether the student should be suspended from the programme. Throughout the training programme, students are immersed in a strong informal educational environment, comprising regular short talks, research reports, journal clubs and ad hoc reading groups; extensive seminar programs in the Unit itself and its neighbours (including ICN , FIL , Psychology at UCL and Birkbeck, Computational Statistics and Machine Learning and Statistical Science ); and attendance and participation in international conferences. Furthermore, the Unit endeavours to function as a single integrated research group, and so students have ready access to all members of the faculty, not just their immediate supervisors.

Applications		The Unit always has openings for exceptional PhD candidates. Applicants should have a strong analytical background, a keen interest in neuroscience and / or machine learning and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics. Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply. Competitive fully-funded studentships are available each year (to both home and overseas students) and the Unit also welcomes students with pre-secured funding or with other scholarship/studentship applications in progress. Applicants are encouraged to apply directly to the Unit in the first instance by forwarding, in PDF or plain text format where possible: their CV, a statement of research interests, transcript(s) for previous degrees, and arranging for three academic referees to forward letters of reference in this format, to admissions@gatsby.ucl.ac.uk, or to the address below. General enquiries should also be directed to this e-mail address. For further details of research interests please visit the unit website. Recruitment for 2010 entry (commencing late September 2010) is now closed. The website will be updated in late 2010 with application details for 2011. Candidates offered a place on the Gatsby Unit programme will be required to meet UCL standard admissions requirements. Details of these can be found under 'Application and Entry' at: http://www.ucl.ac.uk/prospective-students/graduate-study/ Please note there are English language proficiency requirements for international applicants.

FAQs		Please click here for Frequently Asked Questions
Related links		Other related PhD programmes at UCL. UCL Neuroscience PhD UCL CoMPLEX Some relevant Masters programmes. Intelligent Systems Computational Statistics and Machine Learning Neuroscience General information about graduate study at UCL. Information for prospective graduate students at UCL The UCL graduate school

Address		Gatsby Unit Admissions Alexandra House 17 Queen Square London, WC1N 3AR, UK admissions@gatsby.ucl.ac.uk