Digital Medicine
Digital Medicine is intended for doctoral projects whose main contribution is methodological or computational and whose application lies in medicine or the biomedical sciences. Relevant fields include artificial intelligence, epidemiology, statistics, computational biology and scientific computing.
The program is not tied to a particular disease, clinical specialty or data type. It is therefore suitable for projects that develop, evaluate or apply quantitative methods across areas such as structured health records, imaging, clinical notes, prospective cohorts, genetics, or multi-omics.
This page summarises the program-specific training, annual activities and supervision arrangements. General PhD regulations and administrative information are provided by the PhD School.
Is this the right program for my project?
Digital Medicine is usually the appropriate choice when the doctoral project has a substantial methodological or computational component and addresses a clinical or biomedical question.
Projects should normally involve both:
- methodological expertise in areas such as AI, epidemiology, statistics, computational biology, or scientific computing; and
- a clinical or biomedical application area.
Candidates who are uncertain about program assignment should discuss this with their supervisor and the program coordinators before enrolment.
Supervision and Thesis Advisory Committee
Each candidate is supervised by a principal investigator (PI) and guided by a Thesis Advisory Committee (TAC). In this program the TAC must include at least:
- A methodological expert: a PI in AI, epidemiology, medical statistics, informatics, or scientific computing.
- A clinical or biomedical domain expert: a PI from the relevant clinical specialty or biomedical field.
This is a requirement. The methodological member is responsible for the technical standard of the work; the clinical or biomedical member for whether the question, the data and the intended use make sense in practice.
Once a year, each candidate gives a full-length presentation on the state of the thesis to the TAC and receives detailed feedback on progress, methods and next steps. This together with the Digital Medicine Symposium form the program’s annual progress report (see Lectures and Courses below).
Lectures and Courses
The minimum study duration is six semesters. For the program 180 ECTS are required, composed of 160 ECTS for the thesis and 20 ECTS for curricular courses. The 20 ECTS for curricular courses are composed of core subjects (8–10 ECTS), seminars and journal clubs (6 ECTS) and general subjects (4–6 ECTS).
Core subjects provide the methodological training needed for the doctoral project. They cover quantitative methods for study design, the analysis of complex clinical data, and the development and evaluation of models. Candidates select courses according to the needs of their project. Any prerequisites are specified in the course description.
Course schedules, registration, prerequisites, and the current teaching team are published in i-med.inside.
Link to i-med.inside
Seminars and journal clubs provide opportunities for candidates to present and discuss their own research and to critically evaluate the work of others. This block consists of a mandatory annual symposium and progress report (1 ECTS per year), alongside a free choice of journal clubs, seminar series and conference presentations for the remaining credits.
The Digital Medicine Symposium is held once per semester and each candidate attends once per academic year. During the symposium, candidates are asked to present a poster on the current state of their thesis, gaining practice in poster design and concise scientific presentation as well as feedback from peers. The same work is presented in greater depth at a separate TAC meeting, where candidates receive detailed feedback on their progress, methods and next steps. Attendance at the symposium and the TAC meeting together account for the 1 ECTS.
Link to i-med.inside »
General subjects are offered centrally and shared across all program. They cover good scientific practice, research ethics, diversity and gender aspects in medicine, scientific writing, and presentation skills.
Students
This is a new PhD program. Student representatives will be chosen at the start of the 2026/27 academic year.