Postdoctoral Position in Trustworthy Machine Learning in Cancer at the Department of Electrical and Information Technology of Lund University. This position is partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the CanFaster program (Marie Skłodowska-Curie COFUND program).
Over the past decades, we have been witnessing major breakthroughs in the Artificial Intelligence (AI) and machine learning domain, giving rise to many new opportunities and opening up new horizons. In particular, AI and machine learning techniques are actively being considered in the healthcare domain not only for precision decision making through algorithmic data analysis, but also to foster efficiency with respect to resources, staff, time, and expenditures. Today, however, there is a lack of trust in the decisions made by the AI and machine learning techniques. In particular, it has been shown that the state-of-the-art AI and machine learning techniques may have weaknesses with respect to robustness and suffer from systematic biases. Therefore, the adoption of such techniques has to be with extreme care, particularly in the cancer treatment and care domain with so much at stake. This research project focuses on the application and development of a framework based on AI and machine learning techniques for automated decision making in the context of cancer treatment and care pathways, while taking the trust element into account. Therefore, the postdoctoral fellow will be active in the trustworthy machine learning domain, investigating new techniques for reliable decision making in relation to cancer care pathways and treatment outcomes.