Tenure-track faculty position in
Computational Neuroscience / Computational Cognitive Science
Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, UK
APPLICATIONS FOR THIS POSITION ARE NO LONGER ACCEPTED
The official advert for this position can be found here together with further information with details of terms and conditions.
Applications are invited for a University Lectureship (~ US Assistant Professor equivalent) in the broad area of Computational Neuroscience, including Computational Cognitive Science in the Computational and Biological Learning Lab
(CBL). CBL combines expertise in computational neuroscience and cognitive science (Daniel Wolpert
, Máté Lengyel
, Rich Turner
) and machine learning (Zoubin Ghahramani
, Carl Rasmussen
). We particularly encourage applicants who would complement our current research activities. The successful applicant will develop an independent research program, using computational or theoretical approaches to neuroscience, and may combine these approaches with behavioural experiments. Note that although CBL is based in the Engineering Department the appointee does not need to have formal training in engineering.
Informal enquiries may be made to Daniel Wolpert
, Máté Lengyel
or Rich Turner
- Closing date of applications: Monday, 4th March 2013
- Interviews: March 18th & 19th 2013
- Decisions: immediately after interviews
Applications should be sent or emailed to the Secretary of Department (Admin & HR), Department of Engineering, Trumpington Street, Cambridge CB2 1PZ, UK (tel +44 (0) 1223 332615/18 fax +44 (0) 1223 766364, email email@example.com.
Applications should include a completed CHRIS 6 form (parts I and III, which are downloadable from here
) with the names of three referees (references will be taken up only for short-listed candidates), a curriculum vitae and publications list. In addition please include a brief statement of professional, teaching and/or research experience plus your future research plans (no more than a total of two A4 pages).
Short-listed candidates will be invited to visit the Department, give a short seminar/lecture and attend a formal interview.
The Computational and Biological Learning Lab
at the Department of Engineering
uses engineering approaches to understand the brain and to develop artificial learning systems. CBL is a lively and dynamic group of around 40 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 for research talks, on top of various other regular activities, such as reading and journal clubs. Staff and students in computational neuroscience benefit from a world-class machine learning group within CBL. CBL covers research in the following areas:
(Máté Lengyel, Rich Turner & Daniel Wolpert)
- Learning & memory
- Sensorimotor control
- Neural circuits
(Zoubin Ghahramani, Carl Rasmussen & Rich Turner)
- Bayesian statistics
- Reinforcement learning and control
- Nonparametric methods
CBL is part of the Information Engineering Division
of the Department of Engineering. Research pursued in this Division also includes Computer Vision, Control Engineering, Medical Imaging, Signal Processing and Communications, Speech and Language Technology, and Systems Biology. Collaboration between researchers in these various fields is welcomed and encouraged.
The Department of Engineering
has recently named Bioengineering
as one of its four strategic themes. The Department also 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.
Cambridge has a strategic initiative in neuroscience
and there are substantial opportunities for interaction with world-leading research groups to allow an inter-disciplinary approach to computational neuroscience. There are over 200 Principal Investigators in the theme covering research in Developmental Neuroscience, Cellular and Molecular Neuroscience, Systems and Computational Neuroscience, Cognitive and Behavioural Neuroscience, and Clinical and Veterinary Neuroscience.
Researchers with interests in Computational Neuroscience outside of Engineering include Ed Bullmore, Tim Bussey, Stephen Eglen, Nikolaus Kriegeskorte, Simon Laughlin, David Mackay, Hugh Robinson, Lisa Saksida, Wolfram Schultz & Horace Barlow.
Cambridge is a world-leading centre for research into all aspects of Cognitive Neuroscience with groups in the MRC Cognition and Brain Sciences Unit, the Department of Psychology, the Department of Psychiatry, the Department of Physiology, Development and Neuroscience, and the Faculty of Economics.
Almost all undergraduates in Engineering take a 4-year course leading to the MEng degree. In the first two years, courses cover the foundations of engineering common to all of the main disciplines. In the second two years, the courses are modular and become more specialised, especially in the 4th year where courses often include aspects of current research. In the 4th year, students also do a major project
and all staff are able to propose and supervise projects. External funds are not needed to fund students' time spent on these projects, which can range from software development and basic experimentation through to mini-research projects.
Teaching duties are reviewed annually to ensure a fair allocation of load. The teaching responsibilities will include contributing to undergraduate courses, supervising final-year undergraduate projects, and examining and supervising post-graduate students. Responsibilities specifically associated with the new post will primarily involve teaching in neuroscience in the 2nd, 3rd and 4th years.
Department of Engineering
at the University of Cambridge
is a vibrant and leading international centre for research. The two best regarded world rankings (ARWU
) place Cambridge as number 1 outside the USA, and within the first 10 worldwide, for each of technology, physical sciences, and the life sciences. The Department provides excellent administrative support for its 130-strong faculty with 250 technical and administrative support staff.
The Department has six academic divisions
. Collaborations within and across divisions are encouraged which gives the Department greater flexibility in responding to new initiatives.
- Division A: acoustics, energy, fluid mechanics and turbomachinery
- Division B: electrical engineering
- Division C: mechanics, materials and design
- Division D: civil, structural and environmental engineering and sustainable development
- Division E: manufacturing and management
- Division F: information engineering
The University and location
The University of Cambridge is famous for its heritage of scholarship, historic role and magnificent architecture. This heritage supports one of the world's most important centres for teaching and research. The collegiate structure gives a strong sense of community, and the University is at the forefront of international scholarship and research. Cambridge is a particularly welcoming and tight-knit academic community fostered by its unique system of colleges
that cuts across academic disciplines.
The city of Cambridge is in the south east of England, 50 miles north of London (50 mins by train, trains go every half an hour during the day). Cambridge is generally well served by road and rail links, and is within an easy distance of the major London airports.
Cambridge is a particularly good place to live in with families, with abundant green spaces, safe cycle and pedestrian-friendly routes everywhere, and excellent state-funded educational system from the nursery to higher education.