Associate Professor of Machine Learning

Updated: 2 months ago
Location: Oxford, ENGLAND
Deadline: 21 Apr 2017

Applications are invited for the post of Associate Professor (or Professor) of Machine Learning to be held in the Department of Computer Science with effect from 1 October 2017. The successful candidate will also be appointed as Fellow and Tutor in Computer Science at Christ Church College.

The salary for this post is offered on a scale from £45,562 p.a. plus substantial additional benefits including free single accommodation in college, if available, or housing allowance of £13,673 p.a., access to a shared equity scheme, private health insurance and an Official Studentship Allowance of £1,000 p.a. An allowance of £2,655 p.a. would be payable upon award of Full Professor title.

The Department of Computer Science is a vibrant and growing academic department, which has a research profile across the entire spectrum of contemporary computing. The Associate Professor’s research will focus on Machine Learning, and they will contribute to teaching on the Department’s highly successful undergraduate and graduate programmes. Oxford has a strong tradition in Machine Learning, with multiple active faculty members in the Computer Science, Information Engineering, and Statistics departments.

The Associate Professor will be a member of both the University and the College community. They will be part of a lively and intellectually stimulating research community which performs to the highest international levels in research and publications and will have access to the excellent research facilities which Oxford offers. They will have a role to play in the running of the College as a member of the Governing Body and a trustee of the College as a charity.

The successful candidate will hold a doctorate in computer science, or a related subject, will have the ability to teach across a range of computer science subjects, and will also have a proven research record of high quality at international level in the area of machine learning, and experience of research collaborations at both national and international level.

The closing date for applications is 12.00 noon on 21 April 2017. Interviews will be held on 16 May 2017, please allow a full day for these.


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