=========================================================== PhD position on Interactive Causal Explanations for Patient-centric Personalised Health (1.0 FTE, 4yrs.) Institution : Radboud University Nijmegen / TNO, Netherlands Keywords : causal inference, healthcare, explainable AI, machine learning Application deadline : 6 December 2023 Website : https://www.ru.nl/en/working-at/job-opportunities/phd-candidate-interactive-... ===========================================================

Summary Are you interested in applying state-of-the-art causal methods to support patient-centric healthcare? Do you want to work in an interdisciplinary environment collaborating with machine learning experts, cognitive scientists and medical specialists? If so, then this vacancy may be for you!

Description Within our Personalised Care in Oncology https://www.personalisedcareinoncology.nl/ (PersOn) consortium, we are looking for a talented PhD candidate to work on applying principled causal model inference to help patients make informed decisions about their preferred treatment alternatives. We will use modern explainability techniques, such as Causal Shapley values, to translate complex counterfactual predictions into patient-friendly, understandable information, allowing patients to explore the impact of different available treatments. Together with other PhD candidates and postdoctoral researchers in the consortium, you will help build an integrated causal model of the target oncological domain, and use that as a basis for answering interactive `what if' questions tailored to characteristics and preferences of individual patients. You will work with causal model experts, as well as with researchers, healthcare practitioners, and stakeholders in explainable decision support. Your contribution to the project will be both foundational, advancing the state of the art in personalised causal inference, and applied, focusing on user requirements in terms of explanation and justification to help advance shared decision making about personalised healthcare.

We are: The position is part of a collaboration between the Data Science group https://www.ru.nl/datascience/ in the Faculty of Science at the Radboud University, and the Microbiology and Systems Biology research group at the Dutch research institute TNO https://www.tno.nl/en/. Your home base will be the Data Science group, part of the vibrant and growing Institute for Computing and Information Sciences (iCIS) at Radboud University. The group's main research foci are 1) the design and understanding of deep/causal machine learning methods, 2) modern information retrieval and big data, and 3) computational immunology, with a keen eye on applications in other scientific domains, in particular healthcare, as well as industry. Our group currently consists of ca. 50 researchers, including 25 PhDs. In addition, you will work in the Microbiology and Systems Biology research group of the Health, Living and Work unit of the Netherlands Organisation for Applied Scientific Research (TNO), in close collaboration with the data science group of the ICT, Strategy & Policy unit that is working on solutions that enrich information systems and artificial intelligence (AI) with human knowledge and experience. The focus of this group is to optimise health and cure lifestyle-related disease from a systems biology view. The group is a very multidisciplinary team, including biologists, data scientists, bioinformaticians, etc. Both groups strongly promote an open, inclusive and supportive work environment.

What we expect from you: You have an MSc degree in natural science, computer science, mathematics, or a related discipline. You have a strong interest in multidisciplinary research, especially on the interface between artificial intelligence and health. You are highly motivated, open-minded, and determined to obtain a PhD degree. As you will be working in two different research groups, you need to be flexible, communicative and able to work in a multidisciplinary team.

For more information about this vacancy and details on how to apply, see the website (above), or contact: * Dr Tom Claassen, tel: +31 24 3652019, email: tom.claassen@ru.nl mailto:tom.claassen@ru.nl (iCIS) * Dr Jildau Bouwman, tel: +31 88 8661678, email: jildau.bouwman@tno.nl mailto:jildau.bouwman@tno.nl (TNO) ===========================================================