Research Assistant

Royal Holloway, University of London - Computer Science Department

The CLRC and Computer Science department are seeking to recruit a research assistant to work in the area of scalable machine learning of complex models entitled “Exascale Compound Activity Prediction Engine (ExCAPE)”. This is an EU Horizon 2020 project with participation of many big companies like IMEC, INTEL and a number of EU Universities. The position is available from January 2018 and will run until 31 August 2018.

In this project, we consider scalable machine learning algorithms with applications in the field of predicting compound bioactivity for the pharmaceutical industry. There are challenges including imbalanced data, confidence estimation, data standards, model quality and feature diversity. The ExCAPE project is solving these problems by producing state of the art scalable algorithms and implementations for running on future Exascale machines. The RA will work on the developing machine learning algorithms for exascale computers by using HPC programming techniques.

Applicants should have already completed an MSc or PhD degree in a relevant discipline. Applicants should have an excellent track record and good work experience in applying various programming techniques to implement machine learning algorithms. Applicants should be able to demonstrate scientific creativity, research independence, and the ability to communicate their ideas effectively in written and verbal form.

This is a full time and temporary post, available from January 2018 for a fixed term period to 31st August 2018. This post is based in Egham, Surrey, where the College is situated in a beautiful, leafy campus near to Windsor Great Park and within commuting distance from London.

Informal enquiries can be made to Alex Gammerman at A.Gammerman@rhul.ac.uk

To view further details of this post and to apply please visit https://jobs.royalholloway.ac.uk. The RHUL Recruitment Team can be contacted with queries by email at: recruitment@rhul.ac.uk.

Please quote the reference: 0917-361-R

Closing Date: Midnight, 19 December 2017

Interview Date: To be confirmed

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