Survival analysis is a branch of applied statistical modelling and inference which seeks to model time-to-event data, which are very common in medicine. As a PhD candidate, you will carry out research on survival analysis models for heterogeneous patient cohorts or diseases (e.g. frailty or latent class models, with emphasis on high-dimensional data), using mathematical, statistical and information-theoretic methods, as well as methods from statistical physics (e.g. the replica method). This research project is driven by the data analytics needs of modern medicine, which increasingly aims to target treatment to specific patient subgroups. We therefore envisage engaging data analytics in applying our innovations to real medical data. You will be expected to be comfortable working and discussing with researchers from different discipline backgrounds (mathematics, physics, statistics and medicine), and to have affinity for innovative mathematical, statistical and computational modelling as well as medical applications of new models and methods. You will also be expected to contribute to the supervision of MSc projects within the Faculty of Science and/or Radboud university medical center.

• Undergraduate degree, at Merit or Distinction level, in Mathematics, Statistics or Theoretical Physics.
• Genuine affinity for working on medical data.
• Good spoken and written command of the English language.

Fixed-term contract: you will be appointed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years.

• Employment:  40 hours per week.
• The gross starting salary amounts to €2,325 per month, and will increase to €2,972 in the fourth year (salary scale P).
• In addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus.
• Duration of the contract: you will be appointed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years.
• You may expect to be asked to present your work at relevant scientific workshops in due course.
• The intended start date is 28 September 2020.
• You will be able to make use of our Dual Career Service: our Dual Career Officer will assist with family-related support, such as child care, and help your partner prepare for the local labour market and with finding an occupation.
• Are you interested in our excellent employment conditions?

Radboud University

We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 22,000 students and 5,000 employees at Radboud University. And this requires even more talent and collaboration. You have a part to play!

Faculteit der Natuurwetenschappen, Wiskunde & Informatica

Radboud University is a Dutch research-intensive university, with a distinct international character. Within the Faculty of Science, this PhD position will be hosted jointly by the Physics of Machine Learning and Complex Systems group (PMLCS) in the Biophysics Department of Radboud University, under supervision of Prof. Ton Coolen, and by the Biostatistics Department of the Radboud’s university medical center, under supervision of Prof. Kit Roes. These two academic units are already working together. The PMLCS group is led by Bert Kappen and Ton Coolen. Both are trained as theoretical physicists, but over the years, they have worked mostly on applications of mathematical methods from statistical physics and information theory to modelling and inference problems at the interface between physics, biology, data science, computation, and medicine. The group works mainly on six themes: machine learning and inference, quantum computing, medical statistics, control theory, modelling of complex systems, and networks and graphs. The Biostatistics research group within the Department of Health Evidence at the Radboud university medical center, headed by Prof. dr. Kit Roes, has a strong track record in statistical methodology for clinical research in all its facets. Methodological research focuses on innovative designs and analysis of clinical research for rare disorders and (dynamic) prediction of disease courses and outcomes, a focus that fits in well with individual patient-oriented treatment and clinical research with small population sizes.