Centre for Doctoral Training in Artificial Intelligence for Biomedical Innovation PhD with Integrated Study
Awards: PhD with Integrated Study
Study modes: Full-time, Part-time
Funding opportunities
Placements/internships
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 its translation into real-world use. Our programme 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.
Our programme is especially suitable for those with relatively little prior exposure to computer science and mathematics. This includes clinicians, allied health professionals, and biological/biomedical scientists. Our graduates will acquire technical skills from computer science, mathematics, and statistics, and domain knowledge from biomedical and clinical sciences. They will know how to practice responsible and open AI research & innovation, adopt the best practice for minimising the risk of bias in AI, and understand the importance of model explainability for clinical use.
The research programme is organised into four thematic areas, each with an expert theme leader supported by groups of at least twenty project supervisors from across the University:
- AI for Genomic Medicine
- AI for Biomedical Imaging
- AI for Cellular and Molecular Systems Medicine
- AI for Biomedical & Health Informatics
Our programme provides well-rounded training and development, collaboration and engagement opportunities to turn you into a highly competent, sought-after researcher suited to a variety of careers both inside and outside of academia.
Our programme is a 4 year PhD with integrated study, which means it combines PhD research with taught courses, transferrable skills training and partner engagement.
In Years 1-3, you will take a selection of compulsory and elective courses to establish a solid knowledge base to best match your interests and development needs, and to help you conduct innovative and productive research at the highest level.
You will also complete a broader training programme designed to help you develop into an effective and independent critical thinker with valuable transferrable skills. The training includes aspects such as:
- ethics
- responsible research
- entrepreneurship
- patient and public involvement
- communication
Find out more about compulsory and optional courses
We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.
Award | Title | Duration | Study mode | |
---|---|---|---|---|
PhD with Integrated Study | Artificial Intelligence for Biomedical Innovation | 4 Years | Full-time | Programme structure 2024/25 |
PhD with Integrated Study | Artificial Intelligence for Biomedical Innovation | 6 Years | Part-time | Programme structure 2024/25 |
You will complete a 3-month placement dissertation project, within which you will undertake a separate small research project in collaboration with an external partner. This will enable you to experience another environment and/or research challenge/technical area during your studies. The project may take place on-site with the partner organisation but could also be conducted from the University if those arrangements better suit you and the partner organisation.
The exact profile and timing of the placement project will be formulated in consultation between you, the supervisor team and the CDT. Many students will also choose to undertake separate internships during their studies.
You will gain an understanding of key challenges and opportunities for the application of AI in clinical, biomedical, and public health settings. You will gain the skills, knowledge, and experience to develop and implement AI solutions in interdisciplinary research environments and practice responsible research innovation.
- Teaching and learning methods will include traditional lectures, tutorials, and workshops in the various courses as well as masterclasses, hackathons, and group mini-projects.
- Training will be delivered by Edinburgh staff, invited lecturers, staff from industry and external partners, facilities/service staff.
- Entrepreneurship training through “PhD Max”, “Venture Builder Incubator”, and other bespoke training through the Bayes Centre Entrepreneurship team and the programme’s Innovation training lead.
- Outreach and Public Communication Training from specialist external providers including the Alan Turing Institute.
- Public Patient Involvement and Engagement training and working with stakeholders to ensure research is well targeted and developed with the interests of all parties considered.
- Responsible Research & Innovation training in collaboration with the Alan Turing Institute & experts from the University and the CDT’s external partners.
You will be supported by an experienced team of academic and professional service staff. Each year group will have a dedicated mentor who will work closely with our research and training leads, the CDT management group, external advisory board, and partners to support you.
You will be embedded in the vibrant world-class and interdisciplinary research community within the Informatics Forum and Bayes Centre with access to state-of-the-art computational infrastructure through the School of Informatics and Edinburgh Parallel Computing Centre. This includes access to large CPU and GPU cluster compute in the Edinburgh International Data Facility.
Graduates with inter-disciplinary skills and experience at the interface between biomedical and computational science are in huge demand, with a well identified skills shortage in the UK and globally. You will have the opportunity to work directly and learn from external partners in the public and private sectors and will receive bespoke co-delivered career training in the programme.
- To train PhD students to use machine learning approaches to address real-world problems in inter-disciplinary biomedical, clinical, and health research settings.
- To conduct a broad range of co-designed state-of-the-art PhD research projects with external partners in the public and private sector.
- To develop the innovation and entrepreneurship skills of our students through bespoke training programmes and spin-out support.
- To foster ethical, reproducible, and open research practices among our students.
- To provide experience of conducting research in external organisations through 3-month placement projects.
- To promote participation in the programme by students from diverse academic and cultural backgrounds.
These entry requirements are for the 2025/26 academic year and requirements for future academic years may differ. Entry requirements for the 2026/27 academic year will be published on 1 Oct 2025.
A UK 2:1 honours degree, or its international equivalent, in an area related to the topic of the CDT, for example, computer science, AI, cognitive science, mathematics, physics, engineering, biomedical science, biological science, and clinical & public health sciences.
International qualifications
Check whether your international qualifications meet our general entry requirements:
English language requirements
Regardless of your nationality or country of residence, you must demonstrate a level of English language competency which will enable you to succeed in your studies.
English language tests
We accept the following English language qualifications at the grades specified:
- IELTS Academic: total 6.5 with at least 6.0 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
- TOEFL-iBT (including Home Edition): total 92 with at least 20 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
- C1 Advanced (CAE) / C2 Proficiency (CPE): total 176 with at least 169 in each component.
- Trinity ISE: ISE II with distinctions in all four components.
- PTE Academic: total 65 with at least 59 in each component. We do not accept PTE Academic Online.
- Oxford ELLT: 7 overall with at least 6 in each component.
Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, Trinity ISE or PTE, in which case it must be no more than two years old.
Degrees taught and assessed in English
We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:
We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries (non-MESC).
If you are not a national of a majority English speaking country, then your degree must be no more than five years old at the beginning of your programme of study.
Find out more about our language requirements:
Academic Technology Approval Scheme
If you are not an EU, EEA or Swiss national, you may need an Academic Technology Approval Scheme clearance certificate in order to study this programme.
The CDT programme is fully funded and covers a stipend, tuition fees (both UK and overseas) and research and travel grant for 4 years, or 6 years for part-time study.
The funding does NOT cover visa fees and IHS for international students; these costs have to be covered by the student.
Award | Title | Duration | Study mode | |
---|---|---|---|---|
PhD with Integrated Study | Artificial Intelligence for Biomedical Innovation | 4 Years | Full-time | Tuition fees |
PhD with Integrated Study | Artificial Intelligence for Biomedical Innovation | 6 Years | Part-time | Tuition fees |
By applying to the CDT programme you automatically apply for the full funding. There is no need to apply for any additional sources.
Search for scholarships and funding opportunities:
- CDT Manager, Ekaterina Churkina
- Phone: +44 (0)131 651 7112
- Contact: ai4bicdt@ed.ac.uk
- CDT Director, Professor Ian Simpson
- Contact: director.ai4bicdt@ed.ac.uk
- Informatics Graduate School
- 10 Crichton Street
- Central Campus
- Edinburgh
- EH8 9AB
- Programme: Centre for Doctoral Training in Artificial Intelligence for Biomedical Innovation
- School: Informatics
- College: Science & Engineering
Applying
Select your programme and preferred start date to begin your application.
PhD with Integrated Study in Artificial Intelligence for Biomedical Innovation - 4 Years (Full-time)
PhD with Integrated Study in Artificial Intelligence for Biomedical Innovation - 6 Years (Part-time)
Programme start date | Application deadline |
---|---|
8 September 2025 | 20 January 2025 |
We strongly recommend you submit your completed application as early as possible, particularly if you are also applying for funding or will require a visa. We may consider late applications if we have places available.
You must submit two references with your application.
You must submit an application via the EUCLID application portal and provide the required information and documentation.
This will include submission of:
- a Curriculum Vitae (CV)
- a covering letter describing the applicants motivations, interests, and suitability for the CDT programme.
- degree certificates and official transcripts of all completed and in-progress degrees (plus certified translations if academic documents are not issued in English).
- two academic references
Only complete applications will progress forward to the academic selection stage.
Read through detailed guidance on how to apply for the AI4BI CDT:
Find out more about the general application process for postgraduate programmes:
Further information
- CDT Manager, Ekaterina Churkina
- Phone: +44 (0)131 651 7112
- Contact: ai4bicdt@ed.ac.uk
- CDT Director, Professor Ian Simpson
- Contact: director.ai4bicdt@ed.ac.uk
- Informatics Graduate School
- 10 Crichton Street
- Central Campus
- Edinburgh
- EH8 9AB
- Programme: Centre for Doctoral Training in Artificial Intelligence for Biomedical Innovation
- School: Informatics
- College: Science & Engineering