**The information provided on this page was correct at the time of publication (November 2024). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.**
In the MSc by Research or DPhil in Statistics, you will investigate a particular project in depth and write a thesis that makes a contribution to the field. It may be possible to change from an MSc by Research and pursue a DPhil in Statistics. You will acquire a wide range of research and transferable skills, as well as in-depth ...
**The information provided on this page was correct at the time of publication (November 2024). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.** <br/><br/>In the MSc by Research or DPhil in Statistics, you will investigate a particular project in depth and write a thesis that makes a contribution to the field. It may be possible to change from an MSc by Research and pursue a DPhil in Statistics. You will acquire a wide range of research and transferable skills, as well as in-depth knowledge, understanding and expertise in your chosen field of research. You will become part of a vibrant community of researchers. <br/><br/>**MSc by Research**<br/>The Department of Statistics in the University of Oxford is a world leader in research in probability, bioinformatics, mathematical genetics and statistical methodology, including computational statistics, machine learning and data science. Oxford’s Mathematical Sciences submission came first in the UK on all criteria in the 2021 Research Excellence Framework (REF) and in 2016 the department moved to a newly-refurbished building in the centre of Oxford.<br/><br/>Much of the department’s research is either explicitly interdisciplinary or draws its motivation from application areas, ranging from genetics, immunoinformatics, bioinformatics and cheminformatics, to finance and the social sciences. The department is also part of a number of Centres for Doctoral Training (CDT) which admit graduate students; StatML (Modern Statistics and Statistical Machine Learning), an EPSRC CDT in applicable modern statistical theory and methods as well as on the underpinnings of statistical machine learning in association with Imperial; Mathematics of Random Systems: Analysis, Modelling and Algorithms, an EPSRC CDT in the area of probabilistic modelling, stochastic analysis and their applications in association with Imperial and Oxford Mathematics; Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research (SABS R3), an EPSRC CDT focusing on quantitative and predictive research at the interface between the mathematical and physical, and the biological and medical sciences, focussing on industrially relevant challenges in collaboration with 22 pharmaceutical and biotech companies.<br/><br/>You will be expected to acquire transferable skills as part of your training and to prepare a research poster or give a research presentation each year in the department.<br/><br/>You are expected to teach approximately 12 contact hours per year in undergraduate and graduate courses in the department. This is mentored teaching, beginning with simple marking, to reach a point where individual students are leading whole classes of 10 to 12 undergraduate students. You will be encouraged to participate in social events and to take part in public engagement. The department also offers career development events.<br/><br/>**DPhil**<br/>The Department of Statistics in the University of Oxford is a world leader in research in probability, bioinformatics, mathematical genetics and statistical methodology, including computational statistics, machine learning and data science. Oxford’s Mathematical Sciences submission came first in the UK on all criteria in the 2021 Research Excellence Framework (REF) and in 2016 the department moved to a newly-refurbished building in the centre of Oxford. <br/><br/>Much of the department’s research is either explicitly interdisciplinary or draws its motivation from application areas, ranging from genetics, immunoinformatics, bioinformatics and cheminformatics, to finance and the social sciences The department is also part of a number of Centres for Doctoral Training (CDT) which admit graduate students:<br/><br/>**For the full descriptions, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas**
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Course Details
Information
Study Mode
Full-time
Duration
3 Years
Start Date
10/2025
Campus
University of Oxford
Application deadline
Provider Details
Codes/info
Course Code
Unknown
Institution Code
O33
Points of Entry
Unknown
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