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Mathematical Modelling of Random Systems: Analysis, Models and Algorithms EPSRC CDT at University of Oxford - UCAS

University of Oxford

Degree level: Postgraduate

Mathematical Modelling of Random Systems: Analysis, Models and Algorithms EPSRC CDT (Research)

Course options

2023 - 2024
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Course summary

The information provided on this page was correct at the time of publication (October/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 Centre for Doctoral Training (CDT) in Mathematics of Random Systems is a four-year doctoral programme that offers academically outstanding students training in the areas of probabilistic modelling and stochastic analysis at Imperial and Oxford. This course is taking part in a continuing pilot programme to improve the selection procedure for graduate applications, in order to ensure that all candidates are evaluated fairly. For this course, the socio-economic data you provide in the application form will be used to contextualise the shortlisting and decision-making processes where it has been provided. The Mathematics of Random Systems CDT offers a comprehensive four-year doctoral training course in stochastic analysis, probability theory, stochastic modelling, computational methods and applications arising in biology, physics, quantitative finance, healthcare and data science. It provides solid training in core skills related to probability theory, stochastic modelling, data analysis, stochastic simulation, optimal control and probabilistic algorithms. Research topics focus on five foundation areas:

  • Stochastic analysis: foundations and new directions
  • Stochastic partial differential equations
  • Random combinatorial structures: trees, graphs, networks, branching processes
  • Stochastic computational methods and optimal control
  • Random dynamical systems and ergodic theory
and five application areas:
  • Randomness and universal behaviour in physical systems
  • Stochastic modelling and data-driven modelling in finance
  • Mathematical modelling in biology and healthcare
  • Mathematical and algorithmic challenges in data science
  • Mean-field models and agent-based modelling
In the first year, students follow four Core courses on Foundation areas and three elective courses, and choose a main research topic and a research supervisor. This research project will then be expected to evolve into a DPhil thesis in years two to four. 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 as well as regular seminars, workshops and training in transferrable skills such as communication, ethics and team-working. The CDT has multiple industry partners in the areas of data analytics, finance and healthcare who provide funding for DPhil projects linked to their areas of activity. Candidates with an interest in industry-related research projects are encouraged to apply. Industry-funded DPhil projects provide students with the opportunity to actively engage with our industry partners through collaborative research.

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.
Mathematical Modelling of Random Systems: Analysis, Models and Algorithms EPSRC CDT at University of Oxford - UCAS