**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.**
As a DPhil student in Clinical Epidemiology and Medical Statistics, you will spend up to four years in one of the Botnar Research Centre’s many research groups, working on a research project supervised by one of the principal investigators and your supervisory team. You will take part in the extensive training programme specifica...
**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/>As a DPhil student in Clinical Epidemiology and Medical Statistics, you will spend up to four years in one of the Botnar Research Centre’s many research groups, working on a research project supervised by one of the principal investigators and your supervisory team. You will take part in the extensive training programme specifically organised for graduate students within the department.<br/><br/>As a DPhil student in Clinical Epidemiology and Medical Statistics, you will be based in one of the Botnar Research Centre’s many research groups, working on a research project supervised by one of the principal investigators and your supervisory team. You will take part in the extensive training programme specifically organised for graduate students within the department.<br/><br/>This DPhil programme focuses on epidemiology, medical statistics, clinical trials, real world health data, research methodology, artificial intelligence and machine learning, and health economics - aiming to advance healthcare practice and policy to ultimately generate reliable evidence for improving patient care.<br/><br/>You will develop your research skills during your first year (during your first two years if studying part-time), including compulsory attendance at the departments fundamentals in biomedical research lectures. During the first term, in consultation with your supervisor, you will develop a training needs plan. Your training will be tailored to your specific project and personal requirements drawing from the vast range of courses available at Oxford and covering specialist scientific methods and transferable skills. Please note that there is no formal taught component of the DPhil in Clinical Epidemiology and Medical Statistics; however, you will develop your research skills through a range of research training and by attending departmental/institute journal clubs and seminar series.<br/><br/>During the first term there is compulsory attendance at core lectures on a variety of research techniques and research areas covered in the department including:<br/><br/>immunology<br/>inflammation<br/>tissue engineering<br/>clinical trial design<br/>epidemiology<br/>rheumatology<br/>orthopaedics<br/>musculoskeletal diseases.<br/><br/>During your first year if studying full-time (first two years if studying part-time), you will be expected to attend a minimum of three topic-related modules.<br/><br/>As a member of Medical Sciences Graduate School, you will be entitled to attend various workshops run by the Medical Sciences Skills Training programme which are run during term time.<br/><br/>Attendance on a two-day Data Analysis: Statistics Designing Clinical Research and Biostatistics course is compulsory (if you have had no previous statistical training) to assist you with appropriate research design. As a component of your training, you will be expected to work with your supervisory team to write a research-specific literature review within the first year of your studies if studying full-time (first two years if studying part-time).
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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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