Term 1

Milestones in Probability and Statistics

• This module aims to expose students to the whole breadth of probability and statistics, through the discussion and presentation of seminal papers and their impact on the wider subject.
• Students will be trained in reading research papers, working in groups, and presenting research ideas, whilst developing an appreciation of the importance of cross-fertilisation among different disciplines.

Statistical Frontiers

• This module consists of a series of 1-hour presentations on a number of research topics by relevant academics, aiming to introduce students to the research areas active in the department. As part of the assessment structure, it trains student in academic writing of abstracts and papers.

Additional training:

• Research Integrity Training
  • The University provides online research integrity training relevant to all those involved in delivering, supervising or supporting research.
• Graduate Teaching Assistant Training

  • The teaching on several of the Department’s undergraduate courses is supported by tutorial groups and example classes, many of which are led by research students.

Term 2

Students will be expected to choose at least two Graduate Topics modules, each module consisting of three 10-hour graduate-level lecture courses, with themes covering the broad spectrum of research interests in the department. Details of topics will be decided in the summer before the cohort arrives, taking into consideration the interests of the incoming cohort.

Examples of the modules and topics in Term 2 of 24/25 include:

Graduate Topics in Applied Probability and Mathematical Finance

• Topic 1 - Optimal stopping and Dynkin games
• Topic 2 - Merton problem and optimal control
• Topic 3 - Convex minorants of Levy processes

Graduate Topics in Computational Stochastics and Machine Learning

• Topic 1 – Retrospective Simulation
• Topic 2 – Approximate Bayesian Computation
• Topic 3 – Introduction to deep reinforcement learning

Graduate Topics in Probability

• Topic 1 – Interacting Particle Systems
• Topic 2 – Percolation
• Topic 3 – Random graphs

Graduate Topics in Statistics

• Topic 1 – Prediction or Inference, which comes first?
• Topic 2 – Model selection in regression
• Topic 3 – Infectious disease modelling and computational Bayesian statistics