StatML Centre for Doctoral Training (CDT)
StatML is a new Centre for Doctoral Training (CDT) based at Imperial and Oxford. It will train the next generation of researchers in statistics and statistical machine learning, who will 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.
We are seeking candidates for the 2019 cohort of StatML. To ensure consideration in the first round, submit your application online (https://statml.io) by 11 February 2019.
StatML students will benefit from two leading departments at two world class universities – both are consistently rated amongst the world’s top ten universities. Students will be part of these vibrant research environments and will undertake training at both institutions. A proportion of the doctoral projects will be in collaboration with external partners (https://statml.io/index.php/partners/).
Alongside their own research project, students will be part of a cohort that engages in a programme of activities. These will include high-level training in statistics, machine learning, advanced computation as well as training that will help the student to achieve impact with their research. Students will take part in internships and academic placements at international partner universities (https://statml.io/index.php/academic-partners/).
We invite applications from individuals who hold (or expect to receive) a master’s level degree in mathematics, statistics, physics, computer science, engineering, or in a closely related subject. Whilst the programme is set up for full-time study, we welcome applications for part-time study, including from those with established careers or caring responsibilities.
Students will receive 4 years of funding. Eligibility criteria will apply. Normally, EU and UK nationals who satisfy residency requirements are eligible for all funding sources. There are limited funding opportunities for overseas students. However, we encourage applications from everyone with a suitable academic background.
For an informal discussion about the programme, you can contact either Dr Sarah Filippi, firstname.lastname@example.org, Professor Judith Rousseau, email@example.com, or the CDT director, Professor Axel Gandy at firstname.lastname@example.org.
For administrative question, please write to email@example.com.
Guidelines on how to apply can be found at https://statml.io/. Every student will have a home institution (either Imperial or Oxford) and will be working towards a doctoral degree from this institution (PhD at Imperial, DPhil at Oxford). Students will be matched to a home institution during the admissions process.