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Gatsby Computational Neuroscience Unit MPhil/PhD

Students at the Gatsby Unit study toward a PhD in either theoretical neuroscience or machine learning, with minor emphasis in the complimentary 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.

Key Information

Modes and duration

  • Full-time: 4 years

Tuition Fees (2015/16)

UK/EU:
£4,635 (FT)
Overseas:
£21,530 (FT)

Application deadlines

This Phd programme lasts for four years, including a first year of intensive instruction in techniques and research in theoretical neuroscience and machine learning. We only admit new students starting in September. Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit (contact listed in Next steps, right) to see if you need to consider these in your application preparation. All applications for this programme must be made directly to the Gatsby Unit. Please refer to all information on the Gatsby Unit website for how to apply.

Entry Requirements

Applicants must have a strong analytical background, a keen interest in neuroscience or machine learning and a relevant first degree at a munimum of upper second-class UK Bachelor's level or an overseas equivalent, 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.

The English language level for this programme is: Good

Further information can be found on our English language requirements page.

International students

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below.

Select your country:

Overview

The Gatsby Unit is a centre for theoretical neurosciences and machine learning, focusing on unsupervised, semi-supervised and reinforcement learning, neural dynamics, population coding, bayesian (including nonparametric) statistics, kernal methods and applications of these to the analysis of perceptual processing, neural data, natural language processing, machine vision and bioinformatics.

Research areas

  • Analysis of neural data
  • Neural dynamics
  • Perceptual processing of auditory and visual input
  • Population coding
  • Reinforcement learning
  • Statistical machine learning
  • Unsupervised learning

Funding

A number of competitive fully-funded studentships are available each year. These cover payments of full fees, provide a generous stipend and are available to students of any nationality.

More scholarships are listed on the scholarships website

Careers

Most of our graduates go on to postdoctoral positions in academia, although a few students have been known to take up medicine or senior positions in industry. Recent graduates have taken up research posts at institutions such as the University of Cambridge, Princeton, Berkeley, the Peabody Institute at Harvard, Colorado, and ENS Paris and organisations including Microsoft Research and the Wellcome Trust.

Top career destinations for this degree

  • Postdoctoral Researcher, University of Cambridge (2011)
  • Postdoctoral Research Fellow, UCL Wellcome Trust (2010)
  • Researcher, Google DeepMind (2013)
  • Postdoctoral Researcher, Duke University (2012)

Employability

Our students are extremely well trained - we offer a very intense, and very rigorous, programme. They therefore tend to get good jobs; over 90% of our graduate students get postdoctoral positions, and the ones that do get postdoctoral positions tend to go on to faculty positions.

Networking

There are significant networking opportunities both within and external to the Gatsby Unit. Within the Unit there are daily tea talks where members take in in turns to prepare a ten-minute talk to other members of the Unit. The unit also holds regular weekly seminars to which eminent speakers are invited; these are open to other members of the University and there is an opportunity to meet speakers and attendees after the talk. The Gatsby Unit schedule can be viewed online. Students also run their own reading groups and all students have the opportunity to attend relevant conferences and other international events.

Why study this degree at UCL?

This programme provides a unique opportunity for a critical mass of theoreticians to interact closely with each other, including Computer Science, Science, Functional Imaging, Physics, Physiology, Psychology, Neurology, Ophthalmology, Sainsbury Wellcome Centre 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.

Student / staff ratios › 4 staff › 0 taught students › 16 research students

Department: Gatsby Computational Neuroscience Unit

Application and next steps

Applications

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

Who can apply?

Application deadlines

This Phd programme lasts for four years, including a first year of intensive instruction in techniques and research in theoretical neuroscience and machine learning. We only admit new students starting in September. Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit (contact listed in Next steps, right) to see if you need to consider these in your application preparation. All applications for this programme must be made directly to the Gatsby Unit. Please refer to all information on the Gatsby Unit website for how to apply.

For more information see our Applications page.

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