PhD Studentship in Machine Learning for Automated Software Engineering

The Operational Research Group (http://or.eecs.qmul.ac.uk/) within the School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL), invites applications for a fully-funded PhD studentship to work on a project funded by the Engineering and Physical Sciences Research Council.

The DAASE Project (http://daase.cs.ucl.ac.uk/about/) is an EPRSC funded project involving QMUL, University College London, The University of Birmingham, The University of Stirling, and The University of Sheffield. Our industrial partners include Berner and Mattner, BT Laboratories, Ericsson, GCHQ, Honda Research Institute Europe, IBM, Microsoft Research and Motorola UK. It involves around 50 academics working over 6 years with £6.8M funding.

The successful candidate will pursue a course of research investigating the application of computational search methods, to software engineering challenges with a focus on real-world applications. These techniques could include machine learning approaches, big data techniques, and more broadly any metaheuristic, or operational research technique.

DAASE is a highly collaborative project involving 5 UK universities. The successful candidate will have opportunities to visit and work with industrial and other partners and to be fully engaged with the international community through conferences, workshops and other networking activities. This will enhance their training and development and open new opportunities for collaboration and intellectual development. Students will also have the opportunity to engage with researchers within the OR group working on other projects in a variety of application domains.

All nationalities are eligible to apply for this studentship, which will start on 1st September 2018, however an earlier start date is possible for excellent candidates. The studentship is for three years, and covers international student fees as well as a tax-free stipend of around £16,500 per annum.

Candidates are expected to have a first class honors degree or Masters in Computer Science, Mathematics, Operational Research or related discipline, from a UK University or an equivalent standard from an overseas university. The successful candidate must have a strong programming background, as well as good analytical and communication skills. The student is expected to work as part of a team and independently, and to prepare clear reports and research papers. An understanding of mathematical optimisation techniques, heuristic and hyper-heuristic search is highly desirable although not mandatory.

Informal enquiries can be made by email to Dr. John Drake ([Email Address Removed]) and Dr. John Woodward ([Email Address Removed]) who will supervise the project alongside Prof. Edmund Burke. Informal enquiries are strongly encouraged before a candidate submits an application.

For more information and to apply, please visit: http://www.eecs.qmul.ac.uk/phd/apply.php.

The post will be held open until it is filled, so early application is highly advisable.