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Ingrid Kockum

10 months ago

Doctoral (PhD) Student Position in Data-driven Precision Medicine and Diagnostics Karolinska Institutet in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

Karolinska Institutet

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Keywords

Computer Science
Data Science
Machine Learning
Epidemiology
Biology
Statistical Analysis
Network Analysis
Computational Biology
Precision Medicine
Neuropsychology
Medical Science
Multiple Sclerosis
Genetic
Statistics
Bioinformatic
Diagnostic Tool
Large Language Models

About this position

Karolinska Institutet, one of the world's leading medical universities, invites applications for a Doctoral (PhD) student position in Data-driven Precision Medicine and Diagnostics. This opportunity is part of the Data-driven Life Sciences (DDLS) research school, a major Swedish initiative funded by the Knut and Alice Wallenberg Foundation, aiming to train the next generation of researchers in computational and data science for life sciences.

The successful candidate will join a research group conducting world-leading studies on the occurrence and progression of inflammatory diseases, with a particular focus on multiple sclerosis (MS). The group integrates large-scale clinical information with molecular genetics, environmental/lifestyle data, and registry data, leveraging intensive collaborations at local, national, and international levels. The Center for Molecular Medicine provides a vibrant environment with broad expertise in genetics, epidemiology, and close clinical links, offering opportunities for interdisciplinary interaction and collaboration.

The PhD project centers on data-driven precision medicine and diagnostics, involving data integration, analysis, visualization, and interpretation for patient stratification, biomarker discovery, disease risk assessment, diagnosis, drug response, and health monitoring. Research will utilize extensive assets such as omics data, imaging techniques, electronic healthcare records, longitudinal registries, and biobanks. The project aims to unravel genotype-phenotype relationships and MS progression by leveraging one of the largest MS datasets available, and will also generate synthetic data to address data scarcity in rare diseases, facilitating the development of predictive models and enhancing MS research quality.

Advanced network analysis and Large Language Models (LLMs) will be employed to construct and analyze complex networks integrating omic, genotypic, and clinical datasets. The doctoral student will focus on computational tasks, including method development, data handling, quality control, and large-scale data analysis. The research is closely linked to the EU-funded WISDOM project and will be conducted within the DDLS Research School, providing access to a wide range of elective courses and international exchange opportunities.

Eligibility requirements include a master’s degree in computational biology, data science, bioinformatics, or related fields, or equivalent qualifications. Applicants must demonstrate proficiency in English (equivalent to Swedish upper secondary school English B/English 6), strong programming skills in Python, R, and Linux-based software, and experience with machine learning, deep learning frameworks, and high-performance computing (clusters, GPUs). Familiarity with statistical analysis, genetic data, data visualization, omic data analysis, and network theory is advantageous. Good social and communicative skills, ability to collaborate in international teams, and commitment to a productive work environment are essential.

The position offers a full-time doctoral studentship for up to four years, with a contractual monthly salary, free gym access, and medical care reimbursements. The DDLS program provides substantial funding and a creative, inspiring research environment. Applications should be submitted via the Varbi recruitment system, including a personal letter, CV, degree projects, previous publications, and documents certifying eligibility. Selection will be based on subject knowledge, analytical skill, and relevant experience. For further information, contact Mikaela Hernberg (HR Administrator) or Ingrid Kockum (Research group leader).

Application deadline: 2026-01-31. Join Karolinska Institutet and contribute to advancing precision medicine and improving human health!

Funding details

Available

What's required

Applicants must hold a master’s degree in computational biology, data science, bioinformatics, or a related field, or have completed at least 240 credits with 60 at the advanced/master level, or possess equivalent knowledge. Proficiency in English equivalent to Swedish upper secondary school English B/English 6 is required. Strong programming skills in Python, R, and Linux-based software, experience with machine learning, deep learning frameworks, and high-performance computing (clusters, GPUs) are essential. Familiarity with statistical analysis, genetic data, data visualization, omic data analysis, and network theory is advantageous. Applicants should demonstrate good social and communicative skills, ability to collaborate in international teams, and commitment to a productive work environment. Previous experience in international consortia is a plus.

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Professors

Research group leader at Karolinska Institutet

University Name
Country flag

Sweden

Research Interests

Neurology

Immunology

Multiple Sclerosis

Medical Science

Neurological Disorder