PhD positions in AI in Medicine Full-time

PhD Positions In AI In Medicine

Department of Computer Science (DIKU) invites applicants for PhD positions in AI in Medicine. This project is a part of a collaboration between DIKU and Rigshospitalet, and financed by the European Research Council.

The start date is 1 September 2026 or as soon as possible thereafter.

Funding for two PhD positions working on the use of AI in medicine is available. The positions are focused on various aspects of cancer treatment, including AI-assisted diagnosis, treatment planning, and outcome prediction. Depending on the applicant's qualifications, they may work on medical image analysis, clinical report analysis, or theoretical aspects of AI in medicine. The researchers are expected to work in close collaboration with the Department of Radiation Oncology and the Department of Radiology at Rigshospitalet.

The prevalence of cancer remains a global health challenge, with the National Institutes of Health reporting that an estimated 39.5% of individuals will have cancer at some point in their lives. According to the European Society for Radiotherapy and Oncology, approximately half of cancer patients will require radiotherapy (RT) as part of their treatment regimen. However, the curative effects of RT are accompanied by toxicity risks to healthy tissues surrounding the target tumors. Studies indicate that 15–45% of patients across different cancer types experience various radiation-induced toxicities. This project aims to leverage AI capabilities to study the relationships between toxicities and irradiation of anatomical subregions of human organs, pinpointing critical regions that need to be spared to minimize toxicity risks.

These positions are intended for candidates interested in advancing AI in medicine, with a primary focus on medical image analysis. The research spans multimodal data integration, combining imaging with clinical and treatment-related information. While the main application area is cancer diagnosis and treatment planning, the work also includes related domains such as modelling clinician behaviour (e.g., eye-tracking analysis) and methodological development in medical image analysis. The latter is designed to produce broadly applicable techniques that extend beyond specific tasks and contribute to general advances in AI for healthcare. We are looking for committed candidates who are not afraid to ask questions, can navigate a dynamic research environment, and can independently drive a project until models are applied.

In collaboration with Rigshospitalet, Denmark, DIKU is seeking motivated candidates for PhD positions in applied machine learning. The aim of the project is to develop machine learning solutions and apply them for cancer treatment planning. The candidates are expected to have knowledge in computer science, software development proficiency and experience in machine learning.

The project will be hosted by the IMAGE section, which performs research in medical image analysis, machine learning, and computer vision. Our section often works with clinical and industrial partners, so we aim to develop top-level machine learning solutions with a focus on practical applicability. The section is a part of the Department of Computer Science, Faculty of SCIENCE, University of Copenhagen. We are located in Copenhagen.

The supervisor for the positions – Dr. Bulat Ibragimov – is an Associate Professor working in medical image analysis, computer-aided interventions planning, human-AI interaction, and related fields. He has strong collaborative ties with various Danish and international research institutions. The PhD candidates will be asked to spend 3 months of their study at one of such institutions.

We offer creative and stimulating working conditions in a dynamic and international research environment.

Principal supervisor is Bulat Ibragimov, Associate Professor, Department of Computer Science, email: bulat@di.ku.dk.

Clinical co-supervisor is Ivan Richter Vogelius, Professor, Department of Radiation Oncology, email: ivan.richter.vogelius@regionh.dk.

The PhD programme Depending of your level of education, you can undertake the PhD programme as either:

Option A: A three year full-time study within the framework of the regular PhD programme (5+3 scheme) if you already have an education equivalent to a relevant Danish master's degree.

Option B: An up to five-year full-time study programme within the framework of the integrated MSc and PhD programme (the 3+5 scheme), if you do not have an education equivalent to a relevant Danish master´s degree – but you have an education equivalent to a Danish bachelors´s degree.

Qualifications needed for the regular programme To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master's degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. Computer Science, Mathematics, or Biomedical Engineering. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.

Terms of employment in the regular programme Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The terms of employment and salary are in accordance to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Qualifications needed for the integrated MSc and PhD programme If you do not have an education equivalent to a relevant Danish master´s degree, you might be qualified for the integrated MSc and PhD programme, if you have an education equivalent to a relevant Danish bachelor´s degree. Here you can find out, if that is relevant for you: General assessments for specific countries and Assessment database.

Terms of the integrated programme To be eligible for the integrated scholarship, you are (or are eligible to be) enrolled at one of the faculty's master programmes in Computer Science, Mathematics, or Biomedical Engineering.

Students on the integrated programme will enroll as PhD students simultaneously with completing their enrollment in this MSc degree programme.

The duration of the integrated programme is up to five years, and depends on the amount of credits that you have passed on your MSc programme. For further information about the study programme, please see: www.science.ku.dk/phd, “Study Structures”.

Until the MSc degree is obtained, (when exactly two years of the full 3+5 programme remains), the grant will be paid partly in the form of 48 state education grant portions (in Danish: “SU-klip”) plus salary for work (teaching, supervision etc.) totalling a workload of at least 150 working hours per year. When you have obtained the MSc degree, you will transfer to the salary-earning part of the scholarship for a period of two years. At that point, the terms of employment and payment will be according to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in both PhD programmes

• Complete and pass the MSc education in accordance with the curriculum of the MSc programme (ONLY when you are attending the integrated MSc and PhD programme)
• Carry through an independent research project under supervision
• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Teaching and knowledge dissemination activities
• Write scientific papers aimed at high-impact journals
• Write and defend a PhD thesis on the basis of your project

We are looking for the following qualifications:

• Professional qualifications relevant to the PhD project
• Relevant publications
• Relevant work experience
• Other relevant professional activities
• Curious mind-set with a strong interest in machine learning
• Good language skills

Application and Assessment Procedure Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include:

1. Motivated letter of application (max. one page)
2. Your motivation for applying for the specific PhD project/State which PhD project you are applying for.
3. Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
4. Original diplomas for Bachelor of Science or Master of Science and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
5. Publication list (if possible)
6. Reference letters (if available)

The deadline for applications is 17 May 2026, 23