Computational Discovery at University of Oxford - UCAS

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Course summary

**The information provided on this page was correct at the time of publication (November 2022). 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. The DPhil in Computational Discovery is a multidisciplinary programme spanning projects in Advanced Molecular Simulations, Machine Learning and Quantum Computing to develop new tools and methodologies for life sciences discovery. This innovative course has been developed in close partnership between Oxford University and IBM Research. Each research project has been co-developed by Oxford academics working with IBM scientists. Students will have a named IBM supervisor/s and many opportunities for collaboration with IBM throughout the studentship. The scientific focus of the programme is at the interface between Physical and Life Sciences. By bringing together advances in data and computing science with large complex sets of experimental data, more realistic and predictive computational models can be developed. These new tools and methodologies for computational discovery can drive advances in our understanding of fundamental cellular biology and drug discovery. Projects will span the emerging fields of Advanced Molecular Simulations, Machine Learning, and Quantum Computing while addressing both fundamental questions in each of these fields as well as at their interfaces. Students will benefit from the interdisciplinary nature of the course cohort as well as the close interactions with IBM Scientists. After a very short induction period of one or two weeks, during which some basic training is provided, you will start a research project in your academic supervisor’s laboratory. Most laboratories have weekly meetings where members present and discuss their research results with other members of the laboratory. You will also regularly present your work in progress seminars, which are attended by other research groups working in related areas. Whilst working on your research project you will participate in a comprehensive, flexible skills training programme which includes a range of workshops and seminars in transferable skills, generic research skills and specific research techniques. There are also numerous seminars and lectures by local and visiting scientists and you are provided with many opportunities to meet leading scientists.

Assessment method

There are a number of key stages in the research programme. Within a month of starting, you will meet with your academic and IBM supervisors to finalise your project and agree on an initial programme of research. Within the first three months, you will complete an analysis of your training needs with your academic supervisor. Students begin the DPhil in Computational Discovery programme as a probationary research student (PRS). Before the end of their fourth term students are required to apply for Transfer to DPhil Status. A successful transfer of status from PRS to DPhil status will require the submission of a transfer report. Students who are successful at transfer will also be expected to apply for and gain confirmation of DPhil status to show that their work continues to be on track. This will need to done within nine terms of admission. Both milestones normally involve an interview with two assessors (other than your supervisor) and therefore provide important experience for the final oral examination. You will be expected to submit an original thesis of up to 50,000 words after three or, at most, four years from the date of admission. To be successfully awarded a DPhil you will need to defend your thesis orally (viva voce) in front of two appointed examiners.


Entry requirements

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


Fees and funding

Tuition fees

No fee information has been provided for this course

Additional fee information

For complete and up-to-date information about fees and funding for this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.
Computational Discovery at University of Oxford - UCAS