Arian Lundberg

A joint postdoctoral position is available at KTH Royal Institute of Technology and SciLifeLab in Stockholm, Sweden, in collaboration with Golnaz Taheri’s lab. This opportunity is funded by Digital Futures and focuses on the intersection of artificial intelligence, digital health, and cancer research. The research groups involved bring together expertise in AI and machine learning development, medical bioinformatics, biomarker discovery, cancer precision medicine, and clinical translation. The shared goal is to develop innovative tools that can make a real difference for patients, particularly in the field of precision medicine and diagnostics. The position is ideal for candidates with a strong background in computer science, bioinformatics, medical science, or related disciplines, and who are interested in applying AI and machine learning to solve challenges in cancer research and digital health. The collaborative environment at KTH and SciLifeLab offers access to cutting-edge resources and a vibrant research community. The position is fully funded by Digital Futures, though specific details about the stipend or salary are not provided in the announcement. Applicants should have a PhD in a relevant field and demonstrate experience in AI, machine learning, digital health, cancer research, or precision medicine. Strong research skills and the ability to work collaboratively across disciplines are highly valued. The application deadline is February 9th, 2026. Interested candidates are encouraged to review the official LinkedIn announcement for further details and to prepare their application materials accordingly.

KTH Royal Institute of Technology is recruiting a doctoral student for a project in multiomics, machine learning, and cancer bioinformatics at KTH/SciLifeLab in Stockholm. The project sits within the third-cycle subject Bio Biotechnology – Cancer Bioinformatics and focuses on precision medicine, cancer progression, and the tumor microenvironment, with an emphasis on genitourinary cancers. The research will combine bioinformatics-driven analyses, multi-omics data integration, and machine learning methods to investigate factors contributing to tumor progression and their links to cancer progression. The work is especially relevant for candidates interested in cancer biology, computational biology, translational research, and data-intensive biomedical discovery. Collaboration with clinical and translational researchers may be part of the project. Supervision is proposed by Assist Prof. Arian Lundberg and Prof. Cecilia Williams . The successful candidate will join an active research environment at KTH/SciLifeLab in Stockholm and will work in a setting that values independent research, teamwork, and scientific communication. Eligibility requires a second-cycle degree or equivalent qualification according to Swedish doctoral admission rules. A master’s degree in bioinformatics, computational biology, or a related field is required, together with a strong background in cancer biology. Practical skills in Bash, R, and/or Python are essential for analysis and multiomics integration. Candidates must also have strong English communication skills and an English level equivalent to English B/6 . Two academic or research references are required, including one from a previous supervisor. Selection will prioritize candidates who can work independently, collaborate effectively, analyze complex issues, show initiative, and manage multiple tasks. Experience with machine learning, multiomics integration, interdisciplinary research, clinical or patient data, HPC, and bioinformatics pipelines is advantageous. The position is a temporary full-time doctoral appointment with salary according to KTH’s doctoral student salary agreement. Applications must be submitted through KTH’s recruitment system by 2026-09-12 . Required documents include diplomas and transcripts, evidence of language qualifications, a CV, an application letter describing research interests and future goals, and representative publications or technical reports.