Course summary

The PhD/MPhil course is Statistics is delivered by the CDT in Statistics. Unlike many CDTs, this is not dedicated to a single topic, but covers the range of research areas within probability and statistics, to include theoretical and applied probability, mathematical finance, statistical machine learning, computational, methodological, and applied statistics. Our vision is to create a thorough training environment that allows you to develop both depth and breadth of knowledge and skills and fosters innovative and interdisciplinary thinking. We have a dedicated training programme in the first year, designed to optimally prepare you for your PhD project work and opportunities for continuing development through the years. For the CDT in Statistics, first-year training is split into two parts: a common core, aiming to provide you with an overview of research topics and activity in all areas represented within the department as well as to develop fundamental research skills and an optional core, allowing you to choose from of a wide range of advanced graduate modules, designed for PhD students. This optimally prepares you for the specialised work of the PhD project under the supervision of individual faculty members. You will choose your supervisor and research topic during the first year of the programme. PhD training that is not via the CDT and where the student works with a nominated supervisor from day one is available only in cases where this training scheme is required by the student’s funding source. Further details of research interests of faculty members and potential PhD projects can be found on individual staff web pages. Applicants to the CDT do not need a detailed research proposal. However, it will help to indicate your areas of interest in your personal statement, noting that there is no commitment to stay within that area. Applicants who apply for funding from one of the University's scholarship schemes (the Chancellor's International Scholarship or the China Scholarship Council Award) must develop a research proposal in close collaboration with a potential supervisor and are strongly encouraged to contact the department well before applying. This information is applicable for 2025 entry. Given the interval between the publication of courses and enrolment, some of the information may change. It is important to check our website before you apply.