We are seeking a postdoctoral researcher to join the Machine Learning Group (http://mlg.eng.cam.ac.uk ) in the Department of Engineering, University of Cambridge, UK. The position is funded by Samsung. The successful candidate will collaborate with Professor Zoubin Ghahramani, Dr. Jose Miguel Hernandez Lobato, Dr. Isabel Valera and Professor Carl E. Rasmussen, including one PhD student funded by the same grant and Samsung data scientists.
Successful applicants will have or be near to completing a PhD in computer science, information engineering, statistics or a related area, with extensive research experience and a strong publication record in machine learning, ideally with papers in NIPS, UAI, ICML, or AISTATS. Excellent mathematical and programming skills are essential, with experience in two or more of Bayesian methods, deep learning, one-shot learning, semi-supervised learning, active learning.
Key responsibilities include to work on deep learning and Bayesian methods, with an interest in one-shot learning, semi-supervised learning and active learning.
Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and networking with colleagues and students; planning and organising research resources and workshops.
Salary scales - Research Assistant: £25,728 - £30,688 Research Associate: £31,604 - £38,833
Interviews are expected to happen in mid-September 2017 at the Department of Engineering. A skype interview will be possible for applicants who cannot attend in person.
Fixed-term: The funds for this post are available for 24 months in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please ensure that you upload your Curriculum Vitae (CV), including a list of your publucations, and a covering letter in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.
If you have any questions about this vacancy or the application process, contact Mrs. Rachel Fogg, email: firstname.lastname@example.org , Tel: +44 1223 3 32752.
Please quote reference NM12983 on your application and in any correspondence about this vacancy.
The University values diversity and is committed to equality of opportunity.
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