PhD Position in Data-Driven Precision Medicine and Diagnostics (DDLS Program)

Om jobbet

Do you want to contribute to top quality medical research?
Are you motivated to use advanced computational methods, multi-omics data, and AI driven analytics to unravel cancer biology and enable more precise, individualized treatments? Join us at Karolinska Institutet as a DDLS PhD student in Data-Driven Precision Medicine and Diagnostics and contribute to the development of next-generation strategies for understanding and treating chronic lymphocytic leukemia (CLL).

To be a doctoral student means to devote oneself to a research project under supervision of experienced researchers and following an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required.
Department of Molecular Medicine and Surgery
The Department of Molecular Medicine and Surgery (MMK) carries out both preclinical and clinical research within numerous fields. Linked to the Department are approximately 450 researchers, postgraduate students, teachers and technical and administrative staff and we currently have about 150 PhD students. The Department is conducting undergraduate courses for medical, biomedical and biomedical laboratory students.
The research group
You will join the Clinical Genetics Research Group, led by Professor Richard Rosenquist Brandell, at the Department of Molecular Medicine and Surgery, Karolinska Institutet. Our group is located at BioClinicum, Karolinska University Hospital, Solna, and includes an interdisciplinary team of bioinformaticians, computational scientists, molecular biologists and clinical scientists working on large-scale omics and AI driven biomedical research.

We are generating large-scale multi-omics datasets from patients with CLL, including genomics, epigenomics, transcriptomics, and proteomics, complemented with detailed clinical information. Additional multi-omics data will be generated alongside the reuse of published patient derived omics datasets, providing the PhD student access to exceptionally rich, high-quality resources for data-driven discovery.

The group is actively involved in national and international collaborative efforts in CLL. Computational resources include NAISS supercomputing and local HPC. The student will participate in DDLS Research School activities, national workshops, and specialized courses in AI, statistics, and integrative omics.
Your mission
We are announcing a position as a 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 healthcare records, longitudinal patient and population registries and biobanks.
Project Description
CLL is clinically heterogeneous, and predicting disease progression and therapy response remains a major challenge. Despite advances in targeted therapies (e.g., BTK and BCL2 inhibitors), resistance still develops and cannot always be explained by known driver mutations. This creates an urgent need for integrated molecular models that reveal new biomarkers, subtypes, and resistance mechanisms.

This PhD project aims to develop and apply integrative multi-omics and AI-based computational methods to:

• Identify novel molecular subtypes of CLL
• Discover biomarkers associated with progression and treatment response
• Unravel regulatory and causal mechanisms underlying therapy resistance
• Integrate high-dimensional omics data with knowledge graphs, clinical information, and external datasets to generate testable biological hypotheses

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:

have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or

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

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 pageAssessing 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 pageEnglish 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 onlybe certified by thedocumentation requirement for doctoral education.
Skills and personal qualities
To be eligible, you must meet the general and specific entry requirements for doctoral education at Karolinska Institutet, as stated above and also have:

• A master's degree in bioinformatics, computational biology, computer science, engineering, statistics, biomedicine, or a related field
• Demonstrated experience in computational/programming skills (e.g., Python, R)
• Demonstrated experience with omics data analysis (genomics, transcriptomics, proteomics or similar)
• Excellent communication skills in English

Desired merits
• Experience with machine learning, deep learning, or network analysis
• Skills in multi-omics integration or large- scale data processing
• Familiarity with knowledge graphs or graph databases
• Experience with version-controlled, reproducible pipelines (Git, Nextflow, Snakemake , Docker)
• Background in cancer biology or immunology
• Ability to work independently as well as collaboratively in multidisciplinary teams
• Strong interest in data-driven life science, AI methods, and translational research
About the DDLS Program
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 Foundation.

In 2026 the DDLS Research School will be expanded with 25 academic and 7 industrial PhD students. During the DDLS program, more than 260 PhD students and 200 postdocs will be part of the Research School. The strategic research areas are: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology, and biology of infection.

The future of life science is data driven. Will you be part of that change? Then join us in this unique program!
Supervision
You will be supervised by an interdisciplinary team:

Professor Richard Rosenquist Brandell- Clinical genetics, molecular hematology, precision diagnostics

Professor Janne Lehtiö- Proteogenomics, multiomics- integration, bioinformatics

Dr. Leily Rabbani- Bioinformatics, NGS pipelines, machine learning, knowledge graphs

Dr. Daniel Hägerstrand- Molecular biology, large--scale data analysis, functional validation
What do we offer?
Karolinska Institutet provides an inspiring research environment with cutting-edge expertise- in medical science. KI hosts a broad range of interdisciplinary collaborations, modern laboratory and computational facilities, and strong ties to clinical practice. Employees and students have access to an on-site gym, health promotion services, and a vibrant scientific community.
Terms and conditions
The doctoral student will be employed on a doctoral studentship maximum 4 years full-time.


Application process
Submit your application and supporting documents through the Varbi recruitment system. We prefer that your application is written in English, but you can also apply in Swedish.

Your application must contain the following documents:

- A personal letter and a curriculum vitae
- Degree projects and previous publications, if any
- Any other documentation showing the desirable skills and personal qualities described above
- Documents certifying your general eligibility (seeAabove)
- Documents certifying your specific eligibility (seeBabove)
Selection
A selection will be made among eligible applicants on the basis of the ability to benefit from doctoral education. The qualifications of the applicants will be evaluated on an overall basis.

Karolinska Institutet uses the following bases of assessment:

- Documented subject knowledge of relevance to the area of research
- Analytical skill
- Other documented knowledge or experience that may be relevant to doctoral studies in the subject.

All applicants will be informed when the recruitment is completed.

Want to make a difference? Join us and contribute to better health for all