We are looking for a highly motivated and dynamic postdoc for a 2 year position, to commence on 1 October 2026

The Position
The position is a post doc position conducting research in the use of deep learning for the risk of preterm birth based on prenatal ultrasound and clinical data.

Information on the department can be found at: Department of Computer Science DIKU – University of Copenhagen

Our research
We conduct interdisciplinary research with DTU, CAMES and Rigshospitalet on detecting pregnancies at risk of adverse pregnancy outcomes. Especially, we have a program on timely detection of increased risk of spontaneous preterm birth. We use modern machine learning technologies including deep learning, foundation models, and world models. We work in close collaboration with the clinics and commercial partners to develop technologies that will impact the patient care. We use very large nationwide cohorts, and state of the art high performance compute clusters.

Your job
You will work on everything from data collection over machine learning modelling to clinical implementation. Specific emphasis will be on the machine learning component achieving high performance, robust and usable solutions. Special care will be taken to the robustification via use of modern machine learning technologies including foundation models. You will work in a team of machine learning researchers in collaboration with clinical experts.

Profile
We are looking for a highly motivated and enthusiastic scientist with the following competencies and experience:

Essential experience and skills:

You have

• A PhD in Computer science, statistics, or similar with focus on machine learning
• Experience with deep learning and especially CNNs and VITs and the use and training of foundation models
• Published at the best medical image analysis and/or MLÆ conferences or journals
• Interest in following your work all the way to clinical implementation
• Excellent communication skills and written competences

Desirable experience and skills:

• Experience with deep learning
• Experience with use of high-performance computing
• Experience with medical image analysis and preferably in the fetal medicine space
• Experience publishing at the best places
• Experience handling confidential patient data

Place of employment
The place of employment is at the Department of Computer Science, University of Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment.

The University of Copenhagen was founded in 1479 and is the oldest and largest university in Denmark. It is often ranked as the best university in Scandinavia and consistently as one of the top places in Europe. Within computer science, it is ranked number 2 in the European Union according to the Academic Ranking of World Universities (ARWU) 2021. Copenhagen is one of the 10 most livable cities in the world with a rich culture within music, theater and associations. Life for families is made easy by a publicly supported daycare and health care system, dual career opportunities, maternity/parental leave and six weeks of paid annual vacation.

Terms of employment
The average weekly working hours are 37 hours per week. The position is a fixed-term position limited to a period of two years. The starting date is 1 October 2026.

Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 39,700 DKK/approx. 5,300 EUR (April 2026 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18,07 % to your pension fund.

Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.

The position is covered by the Job Structure for Academic Staff at Universities 2020.

Questions
For further information please contact Mads Nielsen; e-mail: [email protected]; Faculty of SCIENCE – University of Copenhagen

Foreign applicants may find this link useful: www.ism.ku.dk (International Staff Mobility).

Application procedure
Your online application must be submitted in English by clicking ‘Apply now’ below. Furthermore, your application must include the following documents/attachments – all in PDF format:

• Motivated letter of application (max. one page).
• CV incl. education, work/research experience, language skills and other skills relevant for the position.
• A certified/signed copy of a) PhD certificate and b) Master of Science certificate. If the PhD is not completed, a written statement from the supervisor will do.
• List of publications.

Deadline for applications: 21 July 2026, 23.59pm CET
We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.

Københavns Universitet giver sine knap 10.000 medarbejdere muligheder for at udnytte deres talent fuldt ud i et ambitiøst, uformelt miljø. Vi sikrer traditionsrige og moderne rammer om uddannelser og fri forskning på højt internationalt niveau. Vi søger svar og løsninger på fælles problemer og gør ny viden tilgængelig og nyttig for andre.

Kontakt
Mads Nielsen
E-mail: [email protected]

Info
Ansøgningsfrist: 21-07-2026

Ansættelsesdato: 01-10-2026

Arbejdstid: Fuldtid

Afdeling/Sted: Department for Computer Science