Dc 11 Msca Doctoral Network Mlcare (Machine Learning Computational Advancements For Personalized Medicine)

The University of Copenhagen will be offering one PhD fellowship for a Doctoral Candidate (DC), starting 1 June 2026 or as soon as possible hereafter. The position is for 36 months and is funded by the MLCARE MSCA Doctoral Network under Horizon Europe’s EU-funded Marie Skłodowska-Curie Actions (MSCA).

The successful applicant will join a multidisciplinary International PhD training network, and will be expected to attend the secondments as well as summer schools and other network training events. The position will be based at the Department of Biology and the Centre for Machine Learning in the Life Sciences (MLLS) at University of Copenhagen (UCPH). We offer creative and stimulating working conditions in a dynamic and international research environment.

Project description

Foundation Models for Genomics and Health Trajectories

This project develops self-supervised foundation models that connect genomic variation with longitudinal health data. By building multimodal embeddings from large-scale databases like UK Biobank and GenBank, the PhD researcher will link genetic profiles to disease outcomes, drug response, and risk patterns. Models will be aligned with known biological pathways and benchmarked for clinical relevance—advancing the use of genomic AI in precision medicine.

Second generation DNA foundation models like AlphaGenome and GPNStar are giving promising results for score disease causing variants beyond in coding regions. These models have not been validated or finetuned explicitly on human variation, but surprisingly can still reason about human variants. Since millions of human whole genome sequences have been made, there is a big untapped potential both for assessing patterns of human variants effects at a population level as well as developing self-supervised finetuning strategies on human data to improve the specificity of DNA foundation models to be even better at reasoning about human disease.

We will work with AlphaGenome, GPNStar and other state of art genome foundation models including DNAmRNA foundation models currently being developed at University of Copenhagen. Finetuning strategies for human dataset as well as perturbation datasets developed with the focus on disease wil be explored. To the degree that it is possible, temporal aspects of disease progression will also be explored.

The outcome of this project will be population studies of DNA foundation models and open source finetuned on human versions of state-of-the-art DNA foundation models. These can be expected to be important components in the future individualised treatment and drug target prediction.

Lead beneficiary (place of employment)

University of Copenhagen. Centre for Machine Learning in Life Sciences, Department of Biology.

Secondments at:

Supervisors

Professor Ole Winther - University of Copenhagen ole.winther@bio.ku.dk

Marie Lisandra Zepeda Mendoza - Novo Nordisk.

Secondment mentors

Dr. Felix Agakov - Pharmatics Limited

Dr. Carlos Loucera - Fundación Pública Andaluza Progreso Y Salud

Who are we looking for?

The ideal candidate has a background in machine learning, with an MSc preferably in bioinformatics, computational biology, or a related field. The candidate has a strong motivation for doing multidisciplinary research as well as for developing machine learning models to advance the state of the art in biological sequence analysis.

You should have a number of the following qualities:

• Curious mindset with a strong interest in the research themes.
• Knowledge and experience in working with protein language models.
• Strong programming skills in Python, with a particular focus on experience in PyTorch.
• Experience with carrying out a bioinformatics workflow pipeline, including thorough data curation, analysis and modeling.
• Experience with Linux, including working in high-performance computing environments.
• Strong background in biology, including knowledge of phylogeny and taxonomy.
• Analytical mindset and ability to work systematically.
• Great ability to work both independently as well as in collaborations.
• Excellent English language skills.
• University-level teaching experience is a plus.

Required qualifications

To be considered for this position you must have:

• Qualifications corresponding to a Danish master’s degree related to the subject area of the project (bioinformatics, computer science, engineering or similar).
• Fluency in English and excellent communication skills.

Eligibility

Applicants will also be required to meet the European Commission’s MSCADoctoral Network eligibility criteria, notably:

• Mobility Rule - Applicants can be of any nationality and must not have resided or carried out their main activity (work, studies, etc.) in Denmark for more than 12 months in the 36 months immediately before the start of their employment at UCPH. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not considered.
• Doctoral Candidate requirement – the applicant must not be in possession of a doctoral degree at the first day of the employment. Researchers who have successfully defended their doctoral thesis but who have not yet been awarded the doctoral degree are not eligible.
• Doctoral Candidate requirement – the applicant must be –at the date of recruitment – formally admitted to a PhD programme leading to the award of a degree in at least one EU Member State or Horizon Europe associated country. For that purpose, candidates must meet the national requirements for doctoral enrolment in the host country. Proof of admission must be provided prior to the start of the contract.
• Be working exclusively for the action.

Evaluated criteria:

• Study records, including Bachelor and Master
• Previous work & research experience
• Letter of motivation
• Letters of recommendation
• Positive attitude, good communication skills
• English proficiency and other languages

Preferred starting date

1 June 2026 or as soon as possible hereafter.

Terms of employment

The employment as PhD fellow is full time and limited to a period of 3 years. Employment is conditional upon successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. Salary, pension and terms of employment are in accordance with the requirements from the European Commission related to the MSCA programme and the agreement between the Danish Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State. The position is covered by the Protocol on Job Structure 2025. Depending on seniority, the monthly gross salary (before taxes) starts at approximately DKK 31,242/approx. EUR 4,193 (November 2025 level) plus pension. (There is a special taxation scheme for foreign researchers which you may be entitled to Introduction - info.skat.dk)

Application

There are two mandatory steps for applicants:

Applications are via the UCPH jobs portal - your application, in English, must be submitted electronically by clicking “Apply now” and include the following documents in PDF format:

• Motivated letter of application/statement of intent (max. one page).
• CV incl. education, experience, language skills and other qualifications relevant for the position.

The deadline for applications is 3 March 2026, 23:59 PM CET.

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

For more information on working and living in Denmark visit http://ism.ku.dk (International Staff Mobility) and https://www.workindenmark.dk.

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

Questions

For further information, applicants may contact the main supervisor Ole Winther by email at ole.winther@bio.ku.dk

Department/Location: Department of Biology / Centre for Machine Learning in Life Sciences (MLLS)

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