Excellent candidates interested in pursuing a PhD are invited to apply for this PhD Studentship in the Department of Computer Science at the University of Warwick. The research topic falls under the general themes of Data Science and Data Systems, with particular emphasis on investigating the cross-fertilization of Statistical Machine Learning and data Systems.

The Computer Science Department at Warwick is a leading department in the UK, having been ranked 2nd among 89 departments in the 2014 UK research evaluation exercise, having the highest quality research output. It is also highly regarded for its research culture, informal environment, excellent students, and beautiful campus.

The research will in general focus on the benefits that SML models and approaches can bear to modern Data Systems, especially for managing large scale data sets, and vice versa.

You will have the opportunity to join a growing, dynamic group, pursuing academic excellence, while balancing work-life demands. You will also have the opportunity to work within the recently established data science division of the department (bringing together systems and SML expertise). Finally you will also have the opportunity to participate in research conducted at the Alan Turing Institute (the UK's institute for research in AI and Data Science) and especially within the recently established "Machine Learning by Systems for Systems" group therein (https://www.turing.ac.uk/research/interest-groups/machine-learning-systems-systems).

Ideally, candidates will have a strong background in distributed systems/platforms for big data, database systems, statistics and machine learning, and strong programming skills coupled with a desire to implement solutions into real-world systems and perform comprehensive experimentations.

Bursaries covering stipend and fees are available.

Candidates are advised to apply as early as possible.

The PhD research will be supervised by Professor Peter Triantafillou.

For more details please contact p.triantafillou@warwick.ac.uk, enclosing a CV and a short description of your relevant background and interests within the research subject.