Closing date: Apply as soon as possible
This studentship is aligned to Swansea University's Medical and Health Care Studies PhD programme.
This is an exciting PhD scholarship offered by two European universities (Université Grenoble Alpes, France and Swansea University, United Kingdom). This studentship will be part of the joint strategy of both these universities regarding Big Data in Health.
The PhD student will develop data-driven methods, from electronic health data in Wales and France, to examine prescription patterns and develop signal detection models by machine learning and data mining techniques, regarding patient safety, new adverse events, known safety issues and possible unknown beneficial effects of drugs, which can be used to improve surveillance from routinely acquired electronic health data. This project uses asthma as an exemplar case, a growing chronic disease affecting around 10% of children in Europe for which international guidelines are established in this specific population. Asthma will be used as a case study in order to develop and test machine learning methods as a means of real time drug surveillance.
The successful candidate is expected to start their PhD studentship in January 2017.
Applicants should have a Master's degree (or equivalent qualification) in Computer Science, Computing, Data Science, Statistics, Epidemiology, Health informatics, Medical Informatics, Bioinformatics or any other related areas.
The successful candidate should also have a good level of English and/or French (spoken and written). Applications from both the Université Grenoble Alpes and Swansea University are welcomed.
Due to funding restrictions, this studentship is open to UK/EU students only.
The studentship covers the full cost of UK/EU tuition fees, plus a tax free stipend (value to be confirmed).
To apply, please complete and return your:
to: Dr Shang-Ming Zhou (email@example.com)
Applicants should apply for this studentship as soon as possible.
Informal enquiries about this studentship are welcome, and may be directed to the academic contacts listed in the Key Information section. Alternatively, you may telephone Dr Zhou on the following number: +44 (0)1792 602580.