Mathematics of Random Systems: Analysis, Modelling and Algorithms (CDT)
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.
Closed to applications for entry in 2026-27. Register to receive an email when applications open (for entry in 2027-28).
- Expected length:
-
- Full time: 4 years
- Expected start date:
-
- Full time:
- English language level:
-
- Standard level required
About the course
You will participate in a comprehensive doctoral training course, which provides solid training in core skills related to probability theory, stochastic modelling, data analysis, stochastic simulation, optimal control and probabilistic algorithms.
Course structure
In your first year, you will follow four courses matching your area of interest, and choose a main research topic and a research supervisor. This research project will then be expected to evolve into your DPhil thesis in years two to four.
Throughout the four years of the course, you will participate in various CDT activities, including CDT social events, 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 and finance 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.
The department offers extensive support to students, from skills training and career development sessions to a variety of social events in a welcoming and inclusive atmosphere. You will have the opportunity to interact with fellow students and other members of your research groups, and more widely across the department. The department aims to offer excellent supervision and provide a stimulating research environment.
Option modules
You will follow four courses matching your area of interest, chosen from a range of topics.
Research areas
You will have the opportunity to undertake research within the specialised themes of this course.
Course details
Entry requirements
For entry in 2026-27