Martin Jacobsson

KTH Royal Institute of Technology is advertising a postdoc position in machine learning for surgical patients within an interdisciplinary research group in AI and machine learning. The project focuses on early prediction of complications using patient characteristics and high-frequency patient data from surgery, with an emphasis on explainable, transparent, well-calibrated AI models that can express uncertainty and detect drift over time. The work is carried out in collaboration with clinicians at Karolinska University Hospital in complex surgery for high-risk patients. The postdoc will work closely with experts in anesthesia and machine learning, and will contribute to software development, retrospective patient-data experiments, and experimental machine learning methods. The role also includes supervising undergraduate and graduate students. Eligibility highlights: a doctoral degree or equivalent foreign degree is required by the time of the employment decision. Relevant backgrounds include machine learning, signal processing, applied mathematics, computer science, biomedical engineering, or related fields. Strong English communication skills and the ability to independently develop software implementations are required. Preferred experience includes recent PhD completion, deep learning experimentation, and student supervision. Funding and appointment: this is a full-time temporary postdoctoral employment for up to two years. The announcement does not specify a stipend amount; salary is monthly. Application: apply via KTH's recruitment system and submit the requested documents, including CV, degree certificates, translations if needed, and a brief statement of research motivation and interests. The deadline is 2026-06-17 .