Fully funded PhD position in: Machine learning in multi-variate data processing / integration and analysis for clinical diagnostics and prognostics
A fully funded PhD position is available in a multi-disciplinary project between the School of Science and the School of Business and Economics, Loughborough University, UK, on the topic of machine learning in multi-variate data processing / integration and analysis for clinical diagnostics and prognostics.
Loughborough University is ranked 11th in the 2016 UK League Table Ranking (http://www.thecompleteuniversityguide.co.uk/loughborough/performance , and is located in Loughborough, a town well connected to London by a 1h20m journey by train.
Research. The application of advanced analytical techniques to the discovery and implementation of human-borne Chemical, Biological, Radiological and Nuclear (CBRN) markers of interest requires large numbers of samples taken from a highly variable sampled population. Efficient progress in this enterprise is limited by the current limits on the speed and sophistication of the data processing and multivariate analysis of the analytical system outputs. This studentship will start the exploration of the boundary between advanced analytical science (sensory capability) and machine learning, including neural and deep learning. It will be part of what is intended to be an enduring collaboration between researchers in Chemistry, Computer Science, Mathematics and Information Science. The supervisory team is composed of Dr. Andrea Soltoggio, expert in Artificial Intelligence and Neural Learning, and Dr. Martin Sykora, expert in Machine Learning, Data Mining and Big Data. The academic team supporting this project will include:
Prof. C. L. Paul Thomas Chemistry, markers and detection
Prof. Tom Jackson, Centre for Information Management, applied and theory based knowledge management
Dr. Iain Phillips, Department of Computer Science, computer networks and high performance computing
Dr. Eugenie Hunsicker, Department of Mathematics, statistical techniques
Working environment. The student, based at the Computer Science Department http://www.cs.lboro.ac.uk, School of Science, will work and collaborate with diverse research groups: the Center for Analytical Science (Chemistry Department) with access to research of the Toxi-triage H2020 project (http://cordis.europa.eu/project/rcn/194860_en.html)), and the Center for Information Management (CIM) http://www.lboro.ac.uk/research/cim/. Loughborough University offers cutting-edge computing capabilities with a Hydra High Performance Computing cluster, a 1956-core 64-bit Intel Xeon cluster supplied by Bull, and GPUs computing capabilities.
Requirements. The ideal candidate holds (or is about to obtain) a first-class honour undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, or has authored publications in recognised conferences/journals. Independent working skills are valued as well as the capability of working in a team. Collegiality and interpersonal skills are essential. Excellent English language skills are highly desired (see requirements here http://www.lboro.ac.uk/international/englang/index.htm)
Period/Scholarship.
Start: January 2016.
Duration: 3 years.
Scholarship: £14,057 per annum plus tuition fees at the UK/EU rate (currently £4,052 p.a.)
Application deadline: 16 November 2015.
Enquiries and applications.
Informal enquiries are encouraged and to be addressed to Dr. Andrea Soltoggio (a.soltoggio@lboro.ac.uk). Interested candidates are invited to submit an application at http://www.lboro.ac.uk/study/apply/research/including a CV, the names and addresses of two referees, and a statement of research interest (maximum 300 words).