PhD on Process and Data Analysis to Support the Patient Discharge Process

PhD on Process and Data Analysis to Support the Patient Discharge Process

Published Deadline Location
24 Jul 1 Oct Eindhoven

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We are looking for a motivated PhD candidate that wants to develop new methods for the exploration, analysis, and prediction of hospital discharge and aftercare.

Job description

Every year, more than 40,000 patients are admitted to the St. Antonius hospital, of which 6,000 patients go home through Care Mediation with home care or to a nursing or care home. At the moment, patients who go to a nursing/care home sometimes spend too long in the hospital because there is no place available yet at a aftercare institution. By indicating the desired capacity in advance at the various aftercare institutions, St. Antonius wants to shorten the unnecessary hospital stay. In this way we try to improve the flow (inflow-flow-outflow) in the hospital.

The candidate is expected to research and develop Process and Data Analytics methods to identify which factors in the process lead to a certain outcome and how early a prediction should be done to provide a certain confidence level and still be useful. He/she develops novel tools & techniques:
  • Develop and validate a prediction model that predicts patients remaining length of stay and after-care needs based on the St. Antonius data.
  • To identify in which point in time the outcome prediction can have the biggest gain.
  • To define a methodology to identify the contributing factors to a certain prediction.

The project is performed within the Process Analytics cluster under the supervision of Dr. Renata Medeiros de Carvalho and Prof.dr. Boudewijn van Dongen. This position is part of a collaboration between the TU/e and the St. Antonius Hospital. The project brings together scientific scholars from Process Analytics (TU/e) and the AI-team from the St. Antonius Hospital which are an essential combination to address the challenges posed.

The Process Analytics research group ( focusses on the interplay between processes, the data these processes generate, the models that are used to describe them, and the systems that support these processes.

The AI-team (3 FTE) from the St. Antonius Hospital is an innovative team that is part of the Business Intelligence department (35 colleagues). The team has specific knowhow on the development and implementation of data science and artificial intelligence solutions in the hospital.


Eindhoven University of Technology (TU/e)


  • You are enthusiastic about research in Process and Data Analytics and AI in a Hospital/Healthcare environment.
  • You have experience with or a strong background in Process Analytics and/or Data Science. Preferably you finished a master's in Computer Science, (Applied) Mathematics, Data Science or Artificial Intelligence.
  • You have strong programming skills in Python and are familiar with libraries like Scikit Learn, Panda's, SciPy, Seaborn etc.
  • Knowledge about data science tooling (Git, Azure DevOps, Visual Studio Code) is a plus.
  • You have good communication skills and are able to work in a multidisciplinary team.
  • You are creative, critical, analytical, hardworking, and persistent.
  • Proficiency in Dutch is mandatory, as well as fluency in English.

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.


  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V32.6795


Eindhoven University of Technology (TU/e)

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De Rondom 70, 5612 AP, Eindhoven

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