项目介绍

2025年4月29日

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.

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.

The research group

The Department of Molecular Medicine and Surgery (MMK) and the research groups of Vascular Surgery and Clinical Physiology are looking for a curious and highly motivated Ph.D. student to join Dr. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery, you will join a diverse research team focused on atherosclerotic plaque instability based on data from the Biobank of Karolinska Endarterectomies (BiKE): the world’s largest resource for molecular studies on carotid atherosclerosis, offering unprecedented opportunities for both scientific and clinical impact. 

The project setting and DDLS 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 isfunded with a total of 3.3 billion SEK (about 290 MUSD) over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.

In 2025 the DDLS Research School will be expanded with the recruitment of 19 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!

The doctoral student project and the duties of the doctoral student

The overall goal of the proposed project is to investigate clinical, diagnostic, and molecular features of atherosclerotic plaque instability using means of data-driven precision tools, seeking to improve on current paradigms for clinical risk predictions and individualized diagnostic paradigms. Improving atherosclerotic risk prediction has been a primary focus of our teams’ efforts over the last couple of decades, seeking insights into pathways steering plaque instability, as well as identifying novel biomarkers improving on clinical routine.

A cornerstone of these developments lies in the Biobank of Karolinska Endarterectomies (BiKE); established by our group and where clinical, radiological, histological, and complete genomic, transcriptomic and proteomic profiling of plaque tissue and plasma exist from over 1000 patients, together representing the world’s largest resource for molecular characterization of human atherosclerosis. The PhD student project will use data available in the BiKE resource to explore the hypothesis surrounding plaque instability, using clinical imaging as general input for the development of data-driven methods to (i) predict molecular expressions, (ii) translate computational insight into patient-behaviour, and (iii) implement both supervised and unsupervised methods to infer stroke risk from pre-operative input data. Work will here be primarily based on data-driven model developments, but will also be closely tied to validation work performed with clinical and experimental colleagues and group members.

As part of an individual research project, you will be responsible for setting up and evaluating data analysis, implementing models and networks, define optimal scientific protocols, and write scientific articles and conference contributions to review and report the results of these investigations. Alongside the research project, the PhD student will work towards meeting the course requirements of the doctoral program, as outlined in the relevant rules and documentation available on the ki.se website.

What do we offer?

As part of the Vascular Surgery and Clinical Physiology teams we offer a unique translational research environment with wide-ranging expertise spanning data-driven imaging,  clinical science, molecular biology, bioinformatics, and biomedical engineering, all working together to improve atherosclerotic and vascular disease diagnostics. Leveraging unique cohorts and biobank data, the student will also be directly involved in cutting-edge data-driven translational science, collaborating with international networks to push causal understanding of atherosclerotic plaque instability from clinical observation, to molecular understanding, and back to an improved diagnostic reality. Herein, participation in international workshops and conferences, as well as potential research visits to collaborating sites will be included in the expected work.

Further, being directly integrated into the DDSL research school, as well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational resources all provide excellent opportunities for ground-breaking research. The successful candidate will be capable of working efficiently and productively within a team, while also developing the professional ability to work independently on their specific project over time

On a larger scale, Karolinska Institutet is one of the world’s leading medical universities, with the vision to provide better health for all. As a doctoral student you will be offered an individual research project, a well-educated supervisor, a vast range of elective courses, the opportunity to work in a leading research group, and explore opportunities for international exchange. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. You will be employed on a doctoral studentship which means that you receive a contractual salary. Employees also have access to our modern gym for free and receive reimbursements for medical care.

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 requirementYou 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.

Your profile

We are looking for a highly motivated, independent, and analytical person, with:

• A degree or the equivalent in scientific data analysis, data science and machine learning, computer science, bioinformatics, engineering physics, biomedicine, or similar
• Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics
• Specific knowledge of big data analysis, quantitative medical image analysis, or application of data-driven methods for clinical application purposes in general and vascular applications in particular is advantageous, but not required.
• Experience from bioinformatic assessment is highly meritorious, but not required
• Experience using experimental cellular or vascular biology is meritorious, but not required.
• Previous experience with scientific data analysis is advantageous, with involvement in previous scientific publications meritorious.

Further, great emphasis will also be placed on personal competence, with an ambitious, systematic, and problem-solving attitude being central to the sought-after candidate. Excellent communication skills in both spoken and written English are a must, as is the ability to interact and work in a translational research team on national or international level. Dedication to open science is also central, with group work focused on open-source developments, data sharing, etc. We invite exceptional individuals from around the world to apply for this exciting opportunity.

Terms and conditions

The doctoral student will be employed on a doctoral studentship maximum 4 years full-time.