KTH Royal Institute of Technology
Top university
Just Landed
New Today
Postdoc in Multi-Omics Machine Learning and Computational Cancer Biology KTH Royal Institute of Technology in Sweden
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Nov 15, 2026
Country
Sweden
University
KTH Royal Institute of Technology
Apply for this position
Keywords
Suggested positions
About this position
KTH Royal Institute of Technology is offering a postdoctoral position in multi-omics machine learning and computational cancer biology within the A Lundberg Lab, which is part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS). The lab is based at SciLifeLab Stockholm and KTH and focuses on computational approaches for cancer precision medicine.
The project centers on understanding the molecular mechanisms behind cancer aggressiveness, metastasis, and treatment resistance. The research combines cancer biology, multi-omics, and computational methods in an interdisciplinary environment with a strong publication record and a clear translational focus.
The successful candidate will work on integrating multiple data modalities, including biological data, clinical/pathological data, and medical imaging, with an emphasis on developing interpretable and biologically meaningful models. Methods highlighted in the advert include machine learning, deep learning, image analysis, computational pathology, multi-omics integration, and foundation models.
The position is aimed at a researcher with strong computational expertise and an interest in applying advanced methods to biomedical questions in cancer. It also offers opportunities to contribute to grant applications, research networks, education, and mentorship.
The environment is centered on interdisciplinary research at KTH and SciLifeLab, with links to the lab’s research profile and the broader KTH academic setting.
Funding details
Available
What's required
A doctoral degree in computer science, machine learning, computational biology, bioinformatics, or a related field is required and must be completed by the appointment decision. Applicants should have a strong research profile in machine learning, deep learning, computational biology, or related computational fields, with interest in cancer or biomedical research. Required skills and experience include programming in Python and/or R, developing and evaluating computational or machine learning methods, solid knowledge of statistics, biostatistics, and multivariate data analysis, excellent written and spoken English, experience with large-scale high-dimensional biological or biomedical datasets and heterogeneous data integration, one or more of multi-omics integration, multimodal machine learning, medical imaging, computational pathology, image analysis, biological data integration, or foundation models, Unix/Linux and high-performance computing, and scientific writing/publications and/or grant applications. Preferred qualifications include a doctoral degree obtained within three years of the deadline, experience with interpretable or explainable ML, cancer biology/genomics or precision medicine, large public or clinical datasets and independent project development, teaching/mentoring/supervision, strong analytical and problem-solving skills, collaborative interdisciplinary work, and a structured working style.
How to apply
Log into KTH’s recruitment system and submit the complete application online. Include a CV, copies of diplomas and grades, translations if needed, and a brief motivation letter of up to two pages describing your interest in A Lundberg lab and how it relates to your background and goals.
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.