Do you want to help shape the future of precision medicine? PredictMe AB, in collaboration with Karolinska Institutet (KI), offers a unique opportunity to pursue an industrial PhD within the national Data-Driven Life Science (DDLS) program.
About the position and the project
As an industrial PhD student, you will be employed by the startup company PredictMe AB while being formally enrolled as a doctoral student at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet (KI). You will also be part of the national DDLS Research School, an initiative by SciLifeLab and the Wallenberg Foundations aimed at educating the next generation of researchers in data-driven life science.
The research project is titled “From Explainable to Actionable and Reversible Epigenetics: A Transformer-Based Foundation Model for DNA Methylation in Longitudinal Cohorts.” The focus is on developing next-generation AI models for the analysis of DNA methylation. Using longitudinal data from, among others, the Swedish Twin Study SATSA, the project aims to move beyond explaining biological age toward identifying modifiable factors that can promote healthy aging.
The Data-Driven Life Science Research School
Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.
In 2026 the DDLS Research School will be expanded with the recruitment of 25 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/
The future of life science is data-driven. Will you be part of that change? Then join us in this unique program!
At the Department of Medical Epidemiology and Biostatistics, we are announcing the position as DDLS PhD student in Data-driven precision medicine and diagnostics.
Data-driven precision medicine and diagnostics covers data integration, analysis, visualization, and data interpretation for patient stratification, discovery of biomarkers for disease risks, diagnosis, drug response and monitoring of health. The precision medicine research is expected to make use of existing strong assets in Sweden and abroad, such as molecular data (e.g. omics), imaging, electronic health care records, longitudinal patient and population registries and biobanks.
Eligibility requirements for doctoral education
In order to participate in the selection for a doctoral position, you must meet the following general (A) and specific (B) eligibility requirements at latest by the application deadline. It is your responsibility to certify eligibility by following the instructions on the web page Entry requirements (eligibility) for doctoral education.
A) General eligibility requirement
You meet the general eligibility requirement for doctoral/third-cycle/PhD education if you:
1. have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or
2. have satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the advanced/second-cycle/master level, or
3. have acquired substantially equivalent knowledge in some other way in Sweden or abroad.*
Follow the instructions on the web page Entry requirements (eligibility) for doctoral education. *If you claim equivalent knowledge, follow the instructions on the web page Assessing equivalent knowledge for general eligibility for doctoral education.
B) Specific eligibility requirement
You meet the specific eligibility requirement for doctoral/third-cycle/PhD education if you:
· Show proficiency in English equivalent to the course English B/English 6 at Swedish upper secondary school. Follow the instructions on the web page English language requirements for doctoral education.
Verification of your documents Karolinska Institutet checks the authenticity of your documents. Karolinska Institutet reserves the right to revoke admission if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action.
(A) and (B) can only be certified by the documentation requirement for doctoral education.
About Karolinska Institutet and the research group
Karolinska Institutet is one of the world’s leading medical universities, with a vision to advance knowledge about life and contribute to better health for all. The department where you will be academically based, MEB, conducts research across a broad spectrum of epidemiology and biostatistics.
The research group focuses on the epidemiology of aging and is involved in a wide range of projects related to biological aging, genetics, omics, pharmacoepidemiology, geriatrics, and precision medicine. More information here: https://ki.se/en/research/research-areas-centres-and-networks/research-groups/molecular-epidemiology-of-aging-sara-haggs-research-group
A key strength of MEB is its strong collaborative culture, where researchers share and co-fund common resources such as advanced IT infrastructure and an applied biostatistics group. The department is located at the Solna campus.
Your responsibilities
· Develop and apply transformer-based foundation models and machine learning methods for large-scale epigenetic datasets
· Integrate longitudinal data and biological prior knowledge into AI models
· Actively contribute to the development of PredictMe’s core product: automated AI-generated health insight reports
· Collaborate closely with the academic research group led by Sara Hägg (KI) and the industry partner led by Mika Gustafsson (PredictMe)
· Attend required courses within DDLS and KI.
· Communicate research findings through scientific publications and presentations at international conferences
What we offer
· A stimulating environment combining academic excellence at KI with the entrepreneurial mindset of PredictMe
· Membership in the DDLS program, providing access to a national and international research network and specialized doctoral courses
· Employment at PredictMe AB with a competitive salary and benefits, alongside doctoral training at MEB
· Access to modern wellness facilities and career support services at KI
Your profile
Required qualifications:
· Master’s degree (or equivalent) in bioinformatics, computer science, epidemiology, biostatistics, or a related field
· Strong programming skills, particularly in Python and/or R
· Experience in machine learning and AI
· Fluency in spoken and written English
· Ability to work independently as well as in interdisciplinary teams
Meritorious qualifications:
· Experience with epigenetic data analysis (DNA methylation) or other omics data
· Experience from an industry or startup environment
· Knowledge of the biology of aging
Application
Your application should include a cover letter describing your motivation, a CV, copies of academic transcripts and degree certificates, and contact information for at least two references. Send this in an email to the contact persons below.
Application deadline: May 31st 2026
Contact: For questions about the project, please contact the main supervisor Sara Hägg (sara.hagg@ki.se) or the industry representative Mika Gustafsson (mika.gustafsson@predictme.se).