The Computational and Biological Learning Lab (CBL) at the Department of Engineering uses engineering approaches to understand the brain and to develop artificial learning systems. Research in computational neuroscience covers learning and memory in perceptual, cognitive, and motor systems.

PhD students in the group have the opportunity to pursue computational studies at the neuronal or behavioural level, or experimental studies of human behaviour using state-of-the-art robotic and virtual reality interfaces, or combine computational and experimental approaches.
The Department of Engineering has recently received the highest research rating in the UK of all science departments and provides excellent training that includes graduate courses in computational neuroscience and machine learning. CBL is a lively and dynamic group around 30 people, and encourages interaction between all members of the lab, including students, postdocs, and faculty. The entire group meets at least three times a week, on top of various other regular activities, such as reading and journal clubs. Students in computational neuroscience benefit from the strong machine learning group within CBL.
Applicants should have
* strong problem solving and mathematical skills,
* a keen interest in neuroscience,
* a relevant first degree, such as 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 University has a number of competitive fully-funded studentships available each year (to students of any nationality) and CBL also welcomes students with pre-secured funding or with other scholarship/studentship applications in progress.
Informal enquiries are welcome to Daniel Wolpert (wolpert(at)eng(dot)cam(dot)ac(dot)uk) or Mate Lengyel (m.lengyel(at)eng(dot)cam(dot)ac(dot)uk).
For more information on CBL see:
For further details of how to apply see:
Applications for 2010 entry should be received no later than 15 December 2009.
Shortlisted applicants will be invited to attend interview in the week starting with 11 January 2010.

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