Are you an aspiring researcher in the field of Computer or Life Sciences? And would you like to delve into the development of new data science methods tailored to the specific challenges of biological datasets? Then you have a part to play as a PhD candidate. By combining simulations and machine learning, you will help us develop new, innovative methods to extract knowledge from data.

Over the past few decades, rapid advances in biotechnology have offered biologists an unprecedented view on the inner workings of the human body. It is now possible to film cells while they are roaming the tissue of living animals, to trace the development and maturation of immune cells circulating the blood, and to measure thousands of genes, proteins or metabolites in single cells – all of which can be done under highly controlled laboratory conditions. Yet despite these advances, learning meaningful things from such rich and diverse datasets remains a major challenge. Contrary to the popular Dutch saying “meten is weten” (“data equals knowledge”), deriving knowledge from such datasets is hard work and requires carefully crafted analysis strategies.

Our group aims to extract meaningful insights from all these types of data (and more!), collaborating closely with both fundamental biologists (who are expanding our knowledge of the human body) and translational biologists (who are bringing this knowledge to clinical practice to benefit patients). In your project, you will combine the arts of simulation and data science/machine learning to help achieve this goal.

Once you have become proficient in the simulation, statistical and machine learning methods used in the field, you will improve upon these approaches and develop your own. To maximise the impact of your work, you will also help us make these methods usable by biologists from other disciplines. Initially you will focus on movement data (‘trajectories’ of moving cells imaged by time-lapse microscopes), but later on in your PhD, you can choose your own focus according to your interests.

You will spend roughly 10 percent of your time (0.1 FTE) helping with the teaching activities in our department. For example, you may be asked to tutor practical assignments, grade coursework, give presentations during classes, or supervise student projects.


  • You hold a Master’s degree in Computer Science, Life Sciences, or another relevant discipline.
  • You might be a biologist who wants to specialise in biomedical data science and machine learning, or a data scientist who would like to enter the fascinating world of biomedical research.
  • You have experience with either data science/machine learning, the analysis and/or simulation of biological data, or a combination thereof – and you are eager to learn more about any of the above-mentioned topics that you are less familiar with.
  • You value innovation, technical rigour, interdisciplinarity, and teamwork.
  • You have good communication skills, allowing you to work in a strongly interdisciplinary setting.

We are

You will join the Computational Immunology Group within the Data Science Section of the Institute for Computing and Information Sciences at Radboud University. We are embedded in a world-class research group in the field of data science and machine learning, with strong ties to the Medical BioSciences department of the Radboudumc medical hospital as well as to collaborating groups abroad.

Our team consists of both men and women with diverse backgrounds – ranging from computer science, mathematics, and computational modelling to biology and medicine. Please see the group’s publication list as well as Inge Wortel’s Google Scholar profile for examples of the kind of research we are involved in and the techniques we use.

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 24,000 students and 5,600 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play!

We offer

  • It concerns an employment for 1.0 FTE.
  • The gross starting salary amounts to €2,541 per month based on a 38-hour working week, and will increase to €3,247 in the fourth year (salary scale P). 
  • You will receive 8% holiday allowance and 8.3% end-of-year bonus.
  • You will be employed 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 (4 year contract).
  • You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
  • Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.

Additional employment conditions

Work and science require good employment practices. This is reflected in Radboud University’s primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

Would you like more information?

For questions about the position, please contact Inge Wortel, Assistant Professor at

Practical information and applying

You can apply until 12 March 2023, exclusively using the button below. Kindly address your application to Inge Wortel. Please fill in the application form and attach the following documents:

  • A letter of motivation.
  • Your CV.
  • A report on a research project you are proud of (on any topic, e.g. your MSc thesis), along with a short (1/2 page) reflection on the skills you developed during that project.

The first round of interviews will take place on week 12.
You would preferably begin employment on 1 April 2023, but this can be negotiated.

We can imagine you’re curious about our application procedure. It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates.

Apply now Application deadline 

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