PhD position - methods for clinical impact assessment of (AI) prediction algorithms

Prediction models are typically developed to predict the presence of a particular condition or outcome now (diagnosis and management) or in the future (prognosis and prevention). The predictive performance of such models is assessed by comparing predicted probabilities from the model to observed outcomes in empirical datasets through calibration and discrimination (supervised learning). But good calibration and discrimination do not guarantee positive impact on decision making, behavioural changes, or health outcomes. Typically this impact is assessed through large randomised studies, but these are expensive, poorly generalizable, and require substantial time investment. Methods for assessing impact of prediction models at the development stage, during which empirical information on effectiveness and impact of these models is not yet available, are lacking or seldomly used and need to be expanded on. Time for a change!

• You will be working interdisciplinary between the fields of epidemiology and health economic evaluation. Your work will focus on updating existing methods, such as decision curve analysis, and on the development of novel methods to assess the impact of prediction models on decision making and health outcomes for which randomised studies are or will not be performed.
• You will be performing evidence synthesis of existing literature, assessing performance of novel study techniques in simulation studies, and performing analyses on real world empirical datasets.
• You will participate in a large multidisciplinary team, attend weekly meetings, provide presentations of your research both during these meetings and (international) conferences, and contribute to education by teaching epidemiology to (medicine) students.

Applicants for this position should have a relevant MSc, for example, in (clinical) epidemiology, health economics, biomedical or health sciences, biostatistics, (applied) data sciences, or artificial intelligence.

You demonstrate a keen interest in the methodology of medical research, have expertise in working with prediction modelling techniques, have experience with programming (e.g., in R), and can work in teams and communicating about your ideas with peers.

Fluency in written and spoken English is required, and fluency in Dutch is an advantage.

The maximum salary for this position (32 - 36 hours) is € 3.824,00 gross per month based on full-time employment.

In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses and career opportunities. The terms of employment are in accordance with the Cao University Medical Centers (UMC).

Department of Epidemiology and Health Economics In this position, you will work and be supervised in the Department of Epidemiology and Health Economics as part of Methods of Epidemiological Research program and Cochrane Netherlands, in the Julius Center at the UMC Utrecht. You will be part of an energetic, enthusiastic team of more than 30 colleagues from very different backgrounds. The Julius Center has an extensive national and international network.