The StatML Centre for Doctoral Training (CDT) is the Imperial-Oxford 4 year doctoral programme to form the next generation of statisticians and machine learners who will be able to develop widely-applicable novel methodology and theory, as well as create application-specific methods, leading to breakthroughs in real-world problems in government, medicine, industry and science.
The research will focus on the development of applicable modern statistical theory and methods as well as on the underpinnings of statistical machine learning. The CDT will provide students with training not only in cutting-edge research methodologies, but also in the development of business and transferable skills – essential elements required by employers in industry and business.
The students will be based either at Imperial College or at the University of Oxford throughout their 4 years which will lead to a PhD degree (Imperial) or a DPhil degree (Oxford). The training is split between both institutions, offering the students to benefit from the vibrant environments of both Imperial and Oxford.
The depth and breadth of expertise of the two departments together is huge, with internationally recognised researchers in computational statistics, high dimensional statistics, machine learning (theory and methods in all three topics), a large variety of applied statistics (biostatistics, astrostatistics, engineering, social science, etc.) and applied probability.
High calibre students will be funded for four years of study, depending on whether they meet the funding criteria. StatML offers at least 10 funded doctoral studentships per year for Home and EU Students (split equally between Imperial and Oxford) and a few non-EU students.