项目介绍

2026年5月24日

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 Department of Medical Epidemiology and Biostatistics conducts research in epidemiology and biostatistics across a broad range of areas within biomedical science. The department is among the largest of its type in Europe and has especially strong research profiles in psychiatric, cancer, reproductive, pediatric, pharmaco, genetic, and geriatric epidemiology, eating disorders, precision medicine, and biostatistics.

Part of the success of our department is due to our collaborative spirit where one factor is that researchers at the Department share and co-finance common resources (e.g., IT and an applied biostatistics group). The department is situated at campus Solna. Further information can be found at http://ki.se/en/meb

The research group

With more than 1.4 million new diagnoses every year worldwide, prostate cancer is one of the most common cancers among men. The prostate cancer research group at Karolinska Institutet is an interdisciplinary and internationally leading research environment focused on improving prostate cancer diagnostics, screening, prognosis, and treatment through precision medicine, machine learning, and artificial intelligence.

The group combines large-scale epidemiological resources, innovative clinical trials, advanced imaging, genomics, digital pathology, and multimodal AI. The research environment includes unique longitudinal datasets such as the STHLM0 register, the STHLM3 and STHLM3-MRI trials, and large-scale archives of digitized pathology slides and prostate MRI examinations.

The group collaborates closely with clinicians, pathologists, radiologists, statisticians, and computer scientists in Sweden and internationally.

The doctoral student project and the duties of the doctoral student

This PhD project focuses on developing next-generation multimodal artificial intelligence systems for prostate cancer. The overall aim is to improve clinical decision-making by integrating information from pathology, radiology, biomarkers, genomics, and clinical data into unified and interpretable AI representations of disease.

The doctoral student will work across several interconnected projects involving:

• Computational pathology foundation models for prostate cancer
• AI models for prostate MRI analysis
• Multimodal representation learning integrating pathology, MRI, genomics, and clinical data
• Transformer-based multimodal fusion models
• Causal and interpretable AI architectures for clinical decision support
• Counterfactual reasoning and disease-state modelling

The work will involve development of deep learning and statistical machine learning methods for large-scale medical imaging and multimodal biomedical data. The student will contribute to model development, validation, and benchmarking using some of the world’s largest prostate cancer datasets.

The project combines methodological AI development with clinically relevant translational research and offers opportunities for collaboration with international research groups and participation in high-impact publications and conferences.

What do we offer?

Choose to work at KI-Ten reasons why
Career support for doctoral students
International staff

• A highly interdisciplinary and internationally competitive research environment
• Access to unique world-leading prostate cancer datasets and clinical trials
• Collaboration with leading experts in AI, statistics, radiology, pathology, and oncology
• Opportunities for international collaboration and exchange
• Access to advanced computing infrastructure for large-scale AI development
• Participation in cutting-edge translational AI research with direct clinical relevance

Karolinska Institutet is one of the world’s leading medical universities. As a doctoral student at KI, you are offered an individual research project, experienced supervisors, doctoral courses, and the opportunity to work within an internationally recognized research group.

A creative and inspiring environment full of expertise and curiosity. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. Karolinska Institutet collaborates with prominent universities from all around the world, which ensures opportunities for international exchanges. 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.

Skills and personal qualities

The applicant should possess a Master’s degree in biostatistics, statistics, data science, bioinformatics, applied mathematics, or a closely related quantitative field.

A strong academic record is highly meritorious. This may include excellent grades, documented distinction in advanced quantitative coursework, or prior training in internationally leading universities or highly ranked quantitative, biomedical, or public-health research environments.

Strong candidates should demonstrate experience in several of the following areas:

• Machine learning and deep learning
• Statistical learning and probabilistic modelling
• Computer vision or biomedical image analysis
• Computational biology or biomedical data science
• Predictive modelling and high-dimensional data analysis
• Transformer architectures and foundation models
• Spatial omics or graph-based modelling
• Natural language processing and clinical AI evaluation

Strong programming skills are required, particularly in Python and/or R. Experience with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, MONAI, or related libraries is highly desirable.

We attach great importance to personal qualities in this recruitment. The applicant should have strong analytical ability, curiosity, creativity, and the ability to work independently as well as collaboratively in interdisciplinary teams. Excellent communication skills in English, both written and spoken, are required.

Previous research experience resulting in scientific reports, publications, open-source software, or conference presentations is highly meritorious.

Terms and conditions

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