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).

Project description

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.

View all positions
We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners. View more
Cookies settings
Privacy & Cookie policy
Privacy & Cookies policy
Cookie name Active
The WASP website uses cookies. Cookies are small text files that are stored on a visitor’s computer and can be used to follow the visitor’s actions on the website. There are two types of cookie:
  • permanent cookies, which remain on a visitor’s computer for a certain, pre-determined duration,
  • session cookies, which are stored temporarily in the computer memory during the period under which a visitor views the website. Session cookies disappear when the visitor closes the web browser.
Permanent cookies are used to store any personal settings that are used. If you do not want cookies to be used, you can switch them off in the security settings of the web browser. It is also possible to set the security of the web browser such that the computer asks you each time a website wants to store a cookie on your computer. The web browser can also delete previously stored cookies: the help function for the web browser contains more information about this. The Swedish Post and Telecom Authority is the supervisory authority in this field. It provides further information about cookies on its website,
Save settings
Cookies settings