Research Assistant/Associate in Machine Learning (Fixed Term)

Updated: about 1 month ago
Location: Cambridge, ENGLAND
Deadline: 14 Sep 2017

We are seeking a Research Assistant/Associate to join the Machine Learning Group ( ) 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 Manuel 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, probabilistic programming, MCMC, graphical models, scalable inference.

Key responsibilities include working on automating machine learning, addressing problems of automatic data preprocessing and modelling, including missing data estimation and outlier identification.

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.

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.

Salary scales: Research Assistant: £25,728 - £30,688 Research Associate: £31,604 - £38,833.

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: , Tel: +44 1223 3 32752.

Please quote reference NM12985 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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