Research Degrees and Studentships
Doctor of Philosophy (DPhil) in Statistics
The Department of Statistics admits doctoral students each year to a programme of instruction and research leading to the Doctor of Philosophy (DPhil) in Statistics degree. A doctorate normally requires between three and four years of full-time study.
DPhil studentship in Genetic network analysis of nitrogen fixation in legume-Rhizobium symbioses now available.
OxWaSP: Statistical Science Centre for Doctoral Training (funded by EPSRC and MRC)
The Statistical Science (EPSRC and MRC Centre for Doctoral Training is a four-year DPhil research programme in the theory, methods and applications of next-generation statistical science for 21st century data-intensive environments and large-scale models.
The programme provides structured training and research experience in the first year, followed by a three-year research project leading to a DPhil. It is the Oxford component of OxWaSP – the Oxford Warwick Statistics Programme.
MSc by Research in Statistics
The MSc by Research in Statistics is similar to a doctorate, but the research project is designed to take 2 to 3 years. It is not intended as a first step towards a DPhil, but rather as an alternative. There are no required lectures, classes or written examinations.
It can be in any of the subject areas for which supervision is available. Those undertaking an MSc by Research are admitted as Probationer Research Students in the same way as those intending to do a DPhil. Thus it is therefore possible to switch between the two. The same standards are applied for admission for the two degrees.
Biomedical applications of Statistics
If you are interested in biomedical applications of statistics, the Systems Approaches to Biomedical Sciences CDT offers fully funded places to study in the Department.
Frequently Asked Questions on the application process
MRC iCASE ‘Enterprise’ Studentships
Four industrial CASE studentships are available for doctoral study at Oxford, to start in October 2018. Each studentship is fully-funded for four years with a stipend of £20,000 p.a., all tuition fees paid, plus a research training support grant. The studentships will be based in the University as part of the Oxford-MRC Doctoral Training Partnership, and will also involve close collaboration with a commercial partner, including at least 3 months working at the company during the course of the D.Phil. project. All applications must be received by 12 noon (UK time) Monday 8 January 2018.
Professor Charlotte Deane from the Department of Statistics will be the lead supervisor for the project below.
Computational methods for rapid structural modelling of antigen–antibody interactions to improve identification of antigen-specific antibodies from Ig-seq repertoire data (commercial partner Kymab Ltd)
The exquisite antigen recognition specificity of antibodies has made them useful as diagnostics, research agents and the most successful class of biopharmaceuticals. The ability to discover better antibody-based therapeutics needs knowledge of the sequence and the 3D shape of individual antibodies within the context of the entire antibody repertoire. Next-generation sequencing methodologies (Ig-seq) can rapidly yield millions of antibody gene sequences and have been used to identify antigen-specific sequences. However, so far the inability to routinely overlay antibody structure on large Ig-seq datasets has limited their potential for antibody drug discovery. Computational methodologies offer a bridge between the two fields by allowing structural annotation of Ig-seq experiments. Here we aim to use this approach to advance our knowledge of the antibodies in health and disease and hence, pave the way for more advanced antibody based therapeutics.
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