Welcome to StatML
A world leading centre for doctoral training shaping the next generation of researchers in statistics and machine learning.
What is StatML?
The EPSRC Centre for Doctoral Training in Statistics and Machine Learning at Imperial and Oxford (StatML) combines two of the UK’s foremost institutions in the field, with a diverse group of industrial and international partners, to shape the next generation of researchers in statistics and machine learning.
We train future researchers, diverse in their backgrounds and perspectives, to develop novel methodology and theory and create application-specific methods, leading to breakthroughs in real-world problems in science, government, medicine, and industry. Our exciting training programme empowers students with the advanced technical and practical skills required to provide real-world impact, solve critical global challenges and create society- changing technologies.
Doctoral programme
StatML is a four-year, fully funded, cohort-based doctoral training centre, with part-time study options available. Our structured programme equips students with the foundational skills and knowledge needed to conduct impactful, ethical, and responsible research. In addition to advanced training in statistics, machine learning, computing, and communication, students engage in first-year mini-projects that allow them to explore different research areas and shape their PhD journey. This is further enriched by a range of scientific and networking events. Learn more about our programme here.
Admissions
StatML Applications for 2026 are now closed.
StatML’s main admission cycle is now closed for 2026-27. Admissions for 2027 will open later in 2026. You can still explore our admission process, timeline and institutional policies.
2026 TechExpert Pilot
StatML is pleased to be part of the TechExpert pilot in 2026, through which we expect to offer stipends of approximately £31,000 for students eligible for home fee status within the 2026 cohort.
The TechExpert pilot aims to strengthen the UK’s innovation pipeline and build a more inclusive, resilient, and high-impact research ecosystem. It will test whether higher stipends make doctoral study a more competitive and financially viable alternative to industry roles, helping retain and upskill talented graduates for future tech careers and supporting pathways back into research.
The programme is delivered by UKRI’s Engineering and Physical Sciences Research Council (EPSRC), with the Biotechnology and Biological Sciences Research Council (BBSRC) and Natural Environment Research Council (NERC), on behalf of the Department for Science, Innovation and Technology (DSIT).
Our students
Discover the breadth of background and research interests of our cohorts by exploring our students’ page.
Harleen Gulati
2025
University of Oxford
Linying Yang
2022
University of Oxford
Alice Chen
2025
University of Oxford
Marcos Tapia Costa
2022
Imperial College London
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Industry & academic partners
StatML has an extensive network of partners across a number of technology sectors and academia to support students and offer additional value to the CDT via internships, placements and studentships.