Deepak's research interests span from pure mathematics to medical statistics to cancer research. On the mathematical front, his research has been in the area of Quantum Groups and Noncommutative Geometry publishing several research papers as well as co-editing a book. In medical statistics, Deepak has been involved in the design and analyses of oncology trials, retrospective analyses and prospective design of cancer studies. His statistical methodology research interests are in the area of Stratified Medicine, a hugely important realm of healthcare where the right patient gets the right treatment at the right time. Besides, Deepak is interested in university mathematics education.
MRC iCASE PhD Studentship
Industrial Partner: Roche Pharmaceuticals
STATISTICAL DESIGN AND ANALYSIS OF CLINICAL STUDIES USING PERSONALISED HEALTHCARE UNDER BIOMARKER UNCERTAINTY
In collaboration with Roche, the PhD project will address an important issue on the role played by continuous biomarkers in the identification of patients most likely to benefit from a particular treatment within the setting of Personalised HealthCare. In order to identify cutoffs that define the targeted subgroup of patients, novel statistical and machine learning methods will be used on large datasets from clinical trials. The research problem shall form a crucial part of the biomarker driven drug development programme from a pharmaceutical industry perspective. A unique opportunity is, therefore, available for embarking on a challenging biomedical statistics research area in a pan academic-industry environment via the MRC iCASE studentship as part of the Warwick DTP in Interdisciplinary Biomedical Research. This project will suit a student with a good undergraduate degree in statistics or a related discipline.
The fully funded studentship starts October 2018. Eligibility and application details available at the Warwick DTP webpages. If interested, please get in touch.
Deadline: 04 March 2018