Phd Student Mathematical Models of Brain Networks

Phd Student Mathematical Models of Brain Networks

Published Deadline Location
29 May 26 Jun Tilburg

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Take your next step in your research career, contribute to research to improve care for patients with brain tumours.

Job description

The department of Neurosurgery offers a position as from October as PhD student mathematical models of brain networks, 36 hours a week

Your Challenge
As a PhD student you will be working on mathematical models of brain networks to simulate the functional effects of tumor removal. You contribute to research that is part of the programme "A personalized care path for brain tumor patients’’. 

  • You perform scientific research at the intersection of network science, computational modeling and cognitive neuroscience.
  • You work with partners with various backgrounds to develop clinical tools to map higher cognitive functions in the peritumoral brain.
  • You present the results of the study in clear, unambiguous reports.
  • You play an active role in all activities of the research team and collaborate with team members.
  • You publish results in scientific journals.
  • You present results at (international) conferences.

Your Professional Environment
You will be part of the research group of the department of Neurosurgery, which participates in the programme Highly Specialised Care & Research programme 2020-2024 , funded by ZonMw (The Netherlands Organisation for Health Research and Development). The aim of this programme is to create a more personalized care path for brain tumor patients before, during and after neurosurgical or Gamma Knife treatment. To improve shared clinical decision making, more extensive and accurate information will be collected, and models will be developed to better predict oncological or functional outcomes (eg, cognitive skills, socio-professional functioning)after (radio)surgical treatment.

The overall programme has two overarching themes: Neuroimaging  (eg, fMRI, DTI) and Cognition. It includes three research projects that are strongly interrelated and whereby a total of 6 PhD candicates will jointly focus on optimization of treatment in the individual brain tumor patient, each from a different perspective. Main partners are Tilburg University (TiU) and Eindhoven University of Technology (TU/e). In addition we are collaborating with several other national and international Universities and University Medical Centers.  At TU/e, you work within the Probability Group of Van der Hofstad that focusses on network science and complex systems, and the Applied Differential Geometry Group of Florack. 

Your Project
Focuses on the development of novel clinical tools to predict higher cognitive functioning in patients with a primary brain tumor in order to reduce the negative effects of brain tumor surgery on cognitive functions. In this part of the project, we want to build personalized brain network models to simulate the functional effects of tumor removal. This will be done by combining clinically obtained structural brain network data of each individual patient (from structural and functional MRI) with network models of brain dynamics. This should allow a virtual exploration of the effect of tumor removal on cognition. You will use network science, image analysis and differential geometry methodology to turn MRI data from patients into functional and structural networks, as well as to investigate the structure of such networks pre- and post-surgery.

The PhD student on this project will work closely with the PhD student on the related project: “Development of clinical tools to map higher cognitive functions in the peritumoral brain.” 

This PhD position will be jointly supervised by dr. Wouter De Baene (TiU), dr. Geert-Jan Rutten (ETZ), prof dr. Remco van der Hofstad (TU/e), prof dr. Luc Florack (TU/e).




  • You have a (research) Master’s degree in a relevant area such as mathematics, computer science, physics, computational modelling or a related discipline.
  • Have interest and/or experience with network science.
  • You have interest in analysing complex imaging data such as resting state fMRI and diffusion weigthed imaging.
  • You possess strong programming skills.
  • You have excellent analytical skills and are highly rigorous.
  • You have good technical understanding (or ability to learn) advanced data analysis and quantitative methods, particularly in the network science domain.
  • You are a fast learner, autonomous and creative.
  • You are highly motivated, work hard and show dedication.
  • You possess good communication skills and are able to work with people from rather diverse backgrounds.
  • You are fluent in English, both spoken and written.

Conditions of employment

Fixed-term contract: 4 years.

The PhD candidate will be employed at both the Elisabeth-TweeSteden Hospital and the Technical University Eindhoven.

  • We offer a full-time (36 hours) agreement / arbeidsovereenkomst voor bepaalde tijd/voor vier jaren. 
  • The selected candidate will start with a contract for four months. Upon a positive outcome of an evaluation, the candidate will be offered an employment contract for the remaining years.
  • Working at ETZ means working in an environment where development and vitality is stimulated. 
  • Salary according to function grouping in FWG 50 with a maximum gross salary, dependent on education and experience, of € 3.664,- on a fulltime basis of 36 hours a week. 
  • A broad package of attractive fringe benefits including an annual holiday allowance and an end-of-year bonus of 8.3%; travel compensation, optional system of additional terms of employment with among others an extensive bike plan.


ETZ (Elisabeth-TweeSteden Ziekenhuis)

Het ETZ (Elisabeth-TweeSteden Ziekenhuis) is een topklinisch opleidingsziekenhuis en traumacentrum. Met drie locaties in Tilburg en Waalwijk is ETZ hét ziekenhuis voor alle inwoners van de regio Midden-Brabant, maar ook (ver) daarbuiten.


  • PhD
  • Natural sciences; Engineering
  • max. 36 hours per week
  • max. €3664 per month
  • University graduate
  • SP 2020.182


Hilvarenbeekse Weg 60, 5022 GC, Tilburg

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