Karolinska Institutet
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PhD Position in Equitable AI for Breast Cancer Screening and Risk Prediction Karolinska Institutet in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
The position is a full-time doctoral studentship for a maximum of four years. The student will be employed by Karolinska Institutet and receive a contractual monthly salary according to KI's doctoral-student salary scale. The position is 100% full time; additional benefits include free access to a modern gym and reimbursement for medical care.
Deadline
Nov 17, 2026
Country
Sweden
University
Karolinska Institutet
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About this position
PhD position in equitable AI for breast cancer screening and risk prediction is available at the Department of Oncology-Pathology, Karolinska Institutet, in Solna, Sweden. The doctoral student will join the Computational Breast Imaging Group, led by Associate Professor Fredrik Strand.
The project investigates whether artificial intelligence systems used in population-based mammography screening perform equitably across population groups and how disparities can be reduced. Research will examine AI cancer-detection and breast-cancer risk-prediction systems across subgroups defined by country of birth and socioeconomic status, compare AI performance with radiologists, and develop fairness-aware models that preserve clinical performance.
The work uses multi-region Swedish screening mammography data linked to cancer outcomes, demographic information, and socioeconomic data. Activities include study design, cohort construction and register linkage, statistical and epidemiological analysis, evaluation of AI on medical images, model development, scientific publication, and conference presentation. Training includes epidemiology, biostatistics, machine learning, and AI fairness.
The main supervisor is Apostolia Tsirikoglou, with Fredrik Strand as co-supervisor. Applicants need a master's degree or equivalent in bioinformatics, biostatistics, or a related quantitative discipline, programming and statistical skills, excellent English, strong analytical ability, and the capacity to work independently and collaboratively. Experience with Swedish registers, health datasets, medical imaging, clinical AI, health equity, or responsible AI is advantageous.
The doctoral studentship is a full-time, four-year maximum appointment with a contractual monthly salary under Karolinska Institutet's doctoral salary scale. Apply through Varbi by 17 November 2026.
Funding details
The position is a full-time doctoral studentship for a maximum of four years. The student will be employed by Karolinska Institutet and receive a contractual monthly salary according to KI's doctoral-student salary scale. The position is 100% full time; additional benefits include free access to a modern gym and reimbursement for medical care.
What's required
Applicants must hold a master's/second-cycle qualification, have completed at least 240 credits including at least 60 credits at advanced/master level, or possess substantially equivalent knowledge. English proficiency equivalent to Swedish upper-secondary English B/English 6 is required. Applicants should have a master's degree or equivalent in bioinformatics, biostatistics, or a related quantitative field; programming skills for data processing and analysis; knowledge of statistical and epidemiological methods; strong analytical ability and interest in AI, medicine, and health equity; ability to work independently and collaboratively in a multidisciplinary team; and excellent written and spoken English. Desirable experience includes population-based register data and record linkage, Swedish national registers, cohort construction, subgroup analyses in large health datasets, large-scale medical imaging data, clinical AI evaluation, health equity, AI fairness, and responsible healthcare AI implementation.
How to apply
Submit the application and supporting documents through the Varbi recruitment system using the Login and apply button. Include a personal letter, CV, degree projects and publications if available, evidence of relevant skills, and documents certifying general and specific doctoral eligibility.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.