KTH Royal Institute of Technology is inviting applications for a Postdoctoral Fellow position in multi-omics machine learning and computational cancer biology. Based at the A Lundberg Lab within SciLifeLab Stockholm, the successful candidate will develop interpretable models to understand cancer aggressiveness, metastasis, and treatment resistance.
Job Overview
| Designation | Postdoctoral Fellow |
| Research Area | Multi-omics Machine Learning, Computational Cancer Biology, Precision Medicine |
| Location | Stockholm, Sweden |
| Employment Type | Temporary (up to 2 years), Full-time |
| Last Date to Apply | November 15, 2026 |
Research Area
The research focuses on cancer precision medicine, combining cancer biology with advanced computational methods. The lab integrates multiple data modalities, including biological, clinical, pathological, and medical imaging data. Key methodologies include machine/deep learning, image analysis, computational pathology, and multi-omics integration.
Job Description
The postdoc will be responsible for developing and applying computational approaches to solve complex problems in oncology. Key responsibilities include:
- Developing interpretable and biologically meaningful machine learning models.
- Integrating heterogeneous data types such as multi-omics and medical imaging.
- Applying foundation models and image analysis to computational pathology.
- Contributing to grant applications, research networks, and mentorship within the lab.
- Collaborating in an interdisciplinary environment at SciLifeLab and KTH.
Eligibility/Qualification
Requirements
- A doctoral degree in Computer Science, Machine Learning, Computational Biology, Bioinformatics, or a related field (must be completed by the time of appointment).
- A strong research profile in machine learning or deep learning with an interest in biomedical applications.
- Proficiency in Python and/or R.
- Solid knowledge of statistics, biostatistics, and multivariate data analysis.
- Excellent written and spoken English.
- Experience working with large-scale, high-dimensional biological datasets.
Preferred Qualifications
- A PhD obtained within the last three years.
- Experience in developing explainable AI (XAI) models.
- Background in cancer genomics or precision medicine.
- Experience with high-performance computing (HPC) and Unix/Linux environments.
How to Apply
Applications must be submitted through the KTH recruitment system. The application should include:
- A comprehensive CV detailing professional experience and knowledge.
- Copies of diplomas and grades from previous university studies (with English or Swedish translations).
- A Motivation Letter (max 2 pages) describing your research interests, why you want to join the A Lundberg lab, and how your previous studies align with the position.
Last Date for Apply
The complete application must be received no later than November 15, 2026, at midnight CET.
Apply Link
Interested candidates can apply directly through the official KTH portal: Official Application Link
