Training Programme
No, this is a 4 year PhD with integrated training so you are applying directly to the PhD programme. Although it is not the aim, it is possible for students to exit the programme early if that is in their best interests. If they have accrued enough credit to satisfy the degree requirements they could exit with an MSc. degree. We have designed our degree programme to allow for maximum flexibility in terms of “exit awards” though we expect most if not all students will exit with a PhD.
You can now view our programme structure on our Training page. The page lists the compulsory and elective courses you can take and how they are organised by year. You can take elective courses throughout the first three years, you progress your PhD research in parallel and then dedicate the final year to your research and writing up your thesis.
You can see an at a glance overview of our training programme and compulsory and elective course choices on our Training page.
You will have seminars, workshops, hackathons, training in RRI/ethics, entrepreneurship/innovation, transferable skills, public engagement. There will be opportunities to undertake internships and there is a compulsory 3-month placement research project. As part of your studentship you will also have a personal budget of £9000 for travel/conferences and research support.
Yes we will be running masterclasses in various biomedical topics, you also have the option to take elective courses for credit (or just to audit) in these areas as well.
Yes the CDT training will include a compulsory credit bearing course in AI Ethics in year 2 as well as a longitudinal RRI and Ethics programme that will run for your entire time in the programme. We have a dedicated RRI/Ethics training lead for the CDT.
Yes we are working with the Innovation Team at the Bayes Centre, Edinburgh Innovations, the Edinburgh Futures Institute to deliver training in entrepreneurship. You will also have the opportunity to join programmes such as “PhD Max” and the “Venture Builder Incubator” run by the Bayes and Data Driven Innovation teams. The University also runs a wide range of other activities outside the CDT to promote innovation.
Our students will have the opportunity to undertake internships which we can assist in arranging through our dedicated Business Development Executive, they will also undertake a 3-month placement research project during their PhD. International students studying on a visa have some restrictions on how they can undertake internships, but we have a lot of experience of working with these regulations as part of our existing UKRI CDT in Biomedical AI. Typically internships are taken in years 2 or 3. The maximum total allowable time to spend on internships during your studies is 12 months. This is a condition of your studentship that is stipulated by our funder, UKRI.
Absolutely. There are many opportunities for students to undertake paid tutoring, marking, and demonstrating roles in courses both within the School of Informatics and beyond. Post-graduate research students play an important role in our teaching and it is an excellent development activity and good for your CV too. There is specific training and support in place from the School of Informatics Teaching Support team to prepare you for these roles if you would like to undertake them.
What are you looking for in an Applicant?
Absolutely. The first year Course “Foundations in Biomedical AI Research” includes a course “Programming in Biomedical Informatics” and masterclasses in various aspects of computation including use of cloud compute, GitHub, Software Engineering and coding in Python and R. Students can also use elective course choices to gain knowledge in computer science, machine learning, statistics and many other topics. Please refer to our Training page for more information. We also have resources to provide tutoring support to students and will run group projects, challenges, and hackathons where students can share their experience of programming and coding.
No. We are recruiting students from diverse disciplinary backgrounds please see our main Application page for details.
We cover elements of this in our application and guidance pages. We’re are looking for applicants from diverse backgrounds who are excited to realise the potential for machine learning and artificial intelligence approaches to tackle challenges in biomedical, clinical, and public health domains.
You will have academic strength in at least one related discipline and will be keen to develop your skills and knowledge to close any gaps in others to successfully undertake cutting edge research during your PhD. In your application we want your enthusiasm to come across and a very strong sense of why you want to study in this area.
Evidence of a commitment to our application domains is important as is evidence of wider reading and additional training that you may have undertaken whether formal or informal. It would be good to see you highlight specific examples of challenges/opportunities that have caught your attention and that you are interested in pursuing. In your application you are asked to indicate which of our research themes you are interested in so aligning your examples with the ones you select would be sensible.
Applicants that are purely interested in methodological development in AI/ML but who do not evidence commitment to biomedical topics will not be well suited to the programme.
Administrative
- UKRI training grant conditions state that: “Both home and International students must be resident in the UK for the majority of their studies and any time spent overseas should be for the purposes of fieldwork/long-term attachment.”
- Students are entitled to annual leave, sick leave, and parental leave. We encourage students to take full advantage of their annual leave.
- Students studying on a student visa must adhere to the conditions of their visa. The University has a student immigration service which has a comprehensive website, you can also contact them for advice.
We aim to recruit 10-12 PhD students in each cohort for 5 years (2024 – 2028). Due to the mix of funding sources used to support studentships in the programme and limitations imposed by UKRI on the proportion of international students allowed to be supported directly by UKRI funds we anticipate up to 50% of our studentships are available for international students.
The CDT research programme is not limited to clinical projects. Our projects will cover a wide range of real-world challenges in biomedical, clinical, and health topics. This means that some projects will be in areas such as drug discovery, genomics, or public health. All projects will need to address applied problems that relate to some phase of the research trajectory between foundational biomedical science (e.g. target, biomarker, disease mechanism etc..) all the way to deployment of AI tools in clinical or public health settings. In short the topics are limited by outcomes intended to translate the potential of AI methods for societal benefit in clinical, biomedical, or public health settings.
Yes, we have fully funded positions available for international students, no additional programme fees payments are needed. We anticipate recruiting on average 6 international students per cohort, though it may vary in any given year based on the quality of applications.
Applicants should note that we are not permitted to cover student visa and immigration health surcharge costs as part of the studentship.
External Partners
Our founding partners are GSK, Roche, AstraZeneca, UCB Celltech, CanonMedical, Fujifilm Diosynth, NEC Labs, Optus, Optima Partners, SICSA, NHS, and NHS-Scotland. We also have a broader grouping of public and private sector partners that have been part of the existing UKTI CDT in Biomedical AI. The number of external partners will grow throughout the course of the CDT.
The training programme includes a compulsory course “Placement Research Project” which is a 3-month project with an external partner. Students will also be able to take internships during their studies; for students on Student Visas there are some restrictions on how these can be taken, but we are experienced dealing with the regulations and will endeavour to give as equal an opportunity to benefit from internships as possible.
Some of our projects are directly proposed by external partners and will involve extensive joint working including periods studying at their research sites. These projects will continue to emerge during our project call process each year. Due to the short recruitment period for the first cohort of students arrangements with external partners will likely be incorporated during the course of the first year of studies.
Resources & Data
Supervisory teams have to ensure that routes to securing the necessary resources are in place in their project proposal application. The CDT management and Research Theme Leads need to be convinced that appropriate plans are in place for the project to be accepted into the programme. We cannot stipulate that data is already in place as the processes for obtaining access to such data (for example UK Biobank) are project based requiring specific application documentation and often training that will involve the PhD student. Groups that, for example, already hold approved projects with such data providers that would cover the proposed PhD project would be in a much better place to secure early access for the student. It is consideration like this that we take into account when approving projects.
The CDT has core budget to support data access costs as well as access to high performance computational resources including CPU, GPU, and high-memory nodes. We have access to the Edinburgh International Data Facility, Edinburgh Parallel Computing Centre, and School of Informatics research compute.
