PhD in Mathematics & Statistics: Generation of synthetic medical histories for clinical decision support – a connected approach

This PhD project proposes to develop a statistical patient record generator capable of generating patient histories which are entirely synthetic, but never-the-less embody the structure, messiness, formats and differing types of data with partially plausible distributions. This studentship is partnered by Toshiba Medical Visualization Systems (TMVS), Edinburgh and the student will spend part of their doctoral studies at partner location in Edinburgh.

The successful candidate will have the chance to work in a very dynamic academic environment offered by the Statistics research group at University of Glasgow, and world-leading medical imaging facilities at TMVS. This proposed studentship offers an exciting opportunity to support the development of leading edge healthcare and medicine support system by constructing a patient data a generator. The student will spend time understanding the statistical distributions of patient data, initially working with real patient data within a NHS Safe Haven at University of Glasgow. The student needs to follow strict confidentiality rules when handling patient data. The student would then codify this understanding into statistical software, which will be able to generate synthetic patient histories on demand.

During the PhD the student will be expected to master a broad range of statistical and computational knowledge, including Big data, Bayesian Analysis, Functional data Analysis, Spatial Statistics and Machine learning in order to tackle the mathematical and computational challenges associated with generating realistic patient histories. The project provides an excellent opportunity to conduct cutting edge methodological development complemented by production of user-friendly software. The successful candidate will need to be comfortable with interfacing with professionals from other disciplines and industry partner and be passionate about their research.

Person specification:

- Passionate about using data analytics for healthcare development, statistical methodology and programming and conducting research
- A BSc/MSc degree in Statistics, computer Science or quantitative discipline
- Willingness to undertake training and career development
- Interest in the challenges in using data to provide affordable and better healthcare
- Interest in developing and evaluating new statistical methods.
- Knowledge of relevant statistical software or programming languages (such as R, MATLab, Python/C)
- Independence of thought and ability to prioritise workload
- Good interpersonal and communication skills (oral and written)

To find more information on how to apply, please click on the "Apply Online" button above/below.