Course structure
Year 1
Term 1: Students follow mandatory coursework involving
Foundations: (2 weeks in Oxford, Sept-Oct)
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Foundations of Stochastic Analysis 8 hours Prof. Ben Hambly (University of Oxford) |
16 hours Prof. Mihai Cucuringu (University of Oxford) |
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Function Spaces and Distribution Theory 8 hours Prof. Antonio Esposito (University of Oxford) |
Tutorials in Stochastic analysis and Data Science
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Four advanced core courses in Term 1 at Oxford and Imperial (Oct-Dec):
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Advanced Topics in Stochastic Analysis and Control Dr Wolfgang Stockinger |
Advanced Topics in Data Science: Deep Learning Prof Jared Tanner |
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Advanced topics in Stochastic Processes Dr Oana Lang |
Simulation Methods and Stochastic Algorithms Prof. Christoph Reisinger |
Terms 2 and 3: Students follow three elective courses chosen from Oxford or Imperial College London.
Each student picks a research topic and a supervisor from the Centre's pool of more than 50 faculty members by end of January and begins working on the supervised research project. Students must choose a supervisor from their home institution.
Years 2, 3 and 4 are dedicated to the students' research project, under supervision of the advisor.
Year 2, Term 1: students progress on their research project is assessed through through a formal exam by two faculty members.
Throughout the 4-year period students participate in cohort activities:
- Monthly CDT seminars/workshops in Oxford and London
- Annual CDT Spring Retreat with tutorials and industry speakers
