Doctoral Student in AI and Clinical Data Science for Breast Cancer
Develop AI-driven data infrastructure to transform multimodal breast cancer data into clinical decision-support benchmarks under expert supervision.
Best for:Best for candidates with a master’s in machine learning, biomedical engineering, or related fields, strong Python programming skills, and a passion for interdisciplinary AI research in healthcare.
Overview
This PhD position at Karolinska Institutet focuses on creating agent-based data infrastructure to structure longitudinal, multimodal breast cancer data into clinical decision-state representations. The project aims to improve AI-supported multidisciplinary decision-making by addressing the complexity of real-world clinical workflows. The doctoral student will work within the Computational Breast Imaging Group, combining expertise in machine learning, data engineering, and biomedical research. The role involves close collaboration with clinical specialists, developing methods for data integration, and contributing to scientific publications and conference presentations. The position is based in Stockholm, Sweden, and offers a collaborative, interdisciplinary environment with access to high-performance computing and large-scale clinical datasets.
What you'll do
- Develop agent-based data infrastructure to transform longitudinal, multimodal breast cancer data into structured clinical decision-state representations.
- Design and implement methods for integrating heterogeneous clinical data sources (imaging, reports, clinical notes, registries).
- Collaborate with clinical specialists to refine research questions and translate findings into practical applications.
- Conduct research using large retrospective breast cancer cohorts linked to national quality registers.
- Publish scientific results in peer-reviewed journals and present findings at international conferences.
- Take an increasingly independent role in formulating research questions, developing methodologies, and managing research projects.
Requirements
Degree required: Master's degree (or equivalent) in image analysis, machine learning, computer science, biomedical engineering, data science, or a related field
Degree offered: PhD
Language: English; proficiency equivalent to English B/English 6 at Swedish upper secondary school level
Instruction: English
- Proficient programming skills in Python
- Experience with machine learning and/or image analysis
- Experience with data engineering, data pipelines, or working with heterogeneous data sources
- Strong analytical ability and interest in interdisciplinary research at the intersection of AI and clinical medicine
- Ability to work independently and collaboratively in multidisciplinary teams
- Excellent written and spoken English proficiency
- Must have been awarded a second-cycle/advanced/master qualification (or equivalent)
- Must demonstrate proficiency in English equivalent to English B/English 6 at Swedish upper secondary school level
- No nationality restrictions, but eligibility must be certified as per Karolinska Institutet’s guidelines
Funding & terms
How to apply
Deadline: 2026-10-20
Submit your application and supporting documents through the Varbi recruitment system. Ensure your application includes a personal letter, CV, degree projects, publications (if any), and documents certifying general and specific eligibility requirements. Applications in English are preferred, but Swedish is also accepted.
- Personal letter
- Curriculum Vitae (CV)
- Degree projects and previous publications (if any)
- Documents certifying general eligibility for doctoral education
- Documents certifying specific eligibility (English proficiency)
- Any additional documentation showing desirable skills or qualities
Contact
Apostolia Tsirikoglou / Fredrik Strand· Supervisors
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