The EPSRC Centre for Doctoral Training in Mathematics of Random Systems: Analysis, Modelling and Algorithms is a partnership between three world-class departments in the area of probabilistic modelling, stochastic analysis and their applications, the Oxford Mathematical Institute, the Oxford Department of Statistics and the Dept of Mathematics, Imperial College London with the ambition of training the next generation of academic and industry experts in stochastic modelling, advanced computational methods and Data Science.
The CDT offers a 4-year comprehensive training programme at the frontier of scientific research in Probability, Stochastic Analysis, Stochastic Modelling, stochastic computational methods and applications in physics, finance, biology, healthcare and data science.
Students receive solid training in core skills related to probability theory, stochastic modelling, data analysis, stochastic simulation, optimal control and probabilistic algorithms. In the first year, students follow four Core courses on Foundation areas as well as three elective courses, and undertake a supervised research project starting the 2nd term. This research project is then expected to evolve into a PhD thesis.
Throughout the four years of the course, students will participate in various CDT activities with their cohort, including a CDT spring retreat, the annual Summer School in Mathematics of Random Systems as well as regular seminars, workshops and training in transferrable skills such as communication, ethics and team-working.
The CDT offers opportunities for research supervised by a pool of more than 40 supervisors from Oxford and Imperial College:
|1. Stochastic analysis: foundations and new directions||6. Randomness and universal behaviour in physical systems|
|2. Stochastic partial differential equations||7. Stochastic modelling and data-driven modelling in finance|
|3. Random combinatorial structures: trees, graphs, networks, branching processes||8. Mathematical modelling in biology and healthcare|
4. Stochastic computational methods and optimal control
|9. Mathematical and algorithmic challenges in data science|
|5. Random dynamical systems and ergodic theory||10. Collective dynamics: Mean-field models and agent-based modelling|
For more information please consult the course information sheet
Industry Partnerships: The CDT has multiple industry partners in the areas of Data Analytics, finance and healthcare. Industry partners provide funding for DPhil projects linked to their areas of activity. Candidates with an interest in industry-related research projects are encouraged to apply. If you are interested in becoming an industry partners of the Centre please contact our Industry Ambassador Dr Katia Babbar.
Funding: The Centre is funded through UK Research and Innovation (UKRI) and multiple industry partners. Successful applicants who are admitted to the Centre will receive full funding for the duration of their 4-year course.
For information on how to apply please follow the link below: