UKRI AI Centre for Doctoral Training in Biomedical Innovation is now accepting applications for September 2026 entry
At least 12 fully funded 4-year PhD studentships are available. Visit our website to see the selection of PhD projects to choose from and find out how to apply.
UKRI AI CDT in Biomedical Innovation
Deadline: 20 January 2026
Register for one of our virtual open days to learn more about the programme and how to apply:
Artificial intelligence has immense potential to tackle the major global health challenges, optimise healthcare systems and improve patient outcomes. The greatest challenge to realising this potential is translation of AI research into real-world use. Our CDT aims to address this challenge by training interdisciplinary researchers who would possess the technical skills, biomedical domain knowledge, and experience developing and implementing innovative AI approaches in the private and public sectors.
This is a flexible cohort based 4-year PhD programme with integrated study that has embedded training in innovation and entrepreneurship. Our model is suitable for both those with relatively little prior exposure to computer science and mathematics, but who contribute essential biomedical knowledge, and those with backgrounds in computer science, mathematics or physics who wish to develop and apply methodologies to biomedicine.
Well-rounded training and development, collaboration and engagement opportunities provided to the students through our programme will turn them into highly competent, sought-after researchers suitable for a variety of careers both inside and outside of academia.
CDT Programme at a Glance
Student support for all needs
The CDT seeks to foster an inclusive and accessible environment where everybody feels supported and respected.
CDT programme offers tailored support and flexible working patterns to meet individual student needs. Studies can be undertaken on a part-time basis to accommodate students wishing to combine their studies with work or personal responsibilities. All CDT studentships are fully funded and have provisions for sick pay, parental leave and disabled students support. We also provide individual coaching sessions to students from underrepresented groups to support their PhD journey and post-PhD career choices.
Funding
Funding covers tuition fees and a stipend (£20,780 in 2025/26) for 4 years, and an individual budget for travel and research costs.
Both UK and international students are eligible for the funding.
For any enquiries please contact the team at [email protected].
At least 12 fully funded 4-year PhD studentships are available. Visit our website to see the selection of PhD projects to choose from and find out how to apply.
UKRI AI CDT in Biomedical Innovation
Deadline: 20 January 2026
Register for one of our virtual open days to learn more about the programme and how to apply:
Artificial intelligence has immense potential to tackle the major global health challenges, optimise healthcare systems and improve patient outcomes. The greatest challenge to realising this potential is translation of AI research into real-world use. Our CDT aims to address this challenge by training interdisciplinary researchers who would possess the technical skills, biomedical domain knowledge, and experience developing and implementing innovative AI approaches in the private and public sectors.
This is a flexible cohort based 4-year PhD programme with integrated study that has embedded training in innovation and entrepreneurship. Our model is suitable for both those with relatively little prior exposure to computer science and mathematics, but who contribute essential biomedical knowledge, and those with backgrounds in computer science, mathematics or physics who wish to develop and apply methodologies to biomedicine.
Well-rounded training and development, collaboration and engagement opportunities provided to the students through our programme will turn them into highly competent, sought-after researchers suitable for a variety of careers both inside and outside of academia.
CDT Programme at a Glance
- Innovative interdisciplinary training programme with a focus on application of novel methods to real-world challenges to improve health outcomes for patients and benefit society.
- Supervision by at least two expert researchers, covering expertise in artificial intelligence and biomedicine from world-leading research groups across the University of Edinburgh.
- Each PhD project features close collaboration with an external partner from the industry or public sector.
- Access to the world-class interdisciplinary research community of the School of Informatics, and state-of-the-art facilities including unique data and computational resources.
- Opportunities for research placements and internships with our UK and international partners across different sectors.
- Tailored training in stakeholder engagement, science communication, career planning, leadership skills, and responsible research AI practices.
- Generous support for entrepreneurship and startup development
- Diverse programme of CDT events including masterclasses, summer schools, hackathons, retreats, and partner engagement days.
Student support for all needs
The CDT seeks to foster an inclusive and accessible environment where everybody feels supported and respected.
CDT programme offers tailored support and flexible working patterns to meet individual student needs. Studies can be undertaken on a part-time basis to accommodate students wishing to combine their studies with work or personal responsibilities. All CDT studentships are fully funded and have provisions for sick pay, parental leave and disabled students support. We also provide individual coaching sessions to students from underrepresented groups to support their PhD journey and post-PhD career choices.
Funding
Funding covers tuition fees and a stipend (£20,780 in 2025/26) for 4 years, and an individual budget for travel and research costs.
Both UK and international students are eligible for the funding.
For any enquiries please contact the team at [email protected].