Velg din region

Velg regionen som passer best for din plassering eller dine preferanser.

Velg ditt nettstedsspråk

Denne innstillingen kontrollerer språket for brukergrensesnittet, inkludert knapper, menyer og all tekst på nettstedet. Velg ditt foretrukne språk for best brukeropplevelse.

Velg språk for stillingsannonser

Velg språkene for stillingsannonser du vil se. Denne innstillingen bestemmer hvilke stillingsannonser som vises for deg.

Eindhoven University of Technology

PhD in judgmental decision making: Combining data and human judgment

2025-05-04 (Europe/Amsterdam)
Lagre jobben

Om arbeidsgiveren

We are an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude.

Besøk arbeidsgiverens side

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

The Industrial Engineering & Innovation Sciences (IE&IS) department combines disciplinary knowledge from the humanities, social sciences and technical sciences to solve the complex problems of industries and society. We collaboratively focus on and create responsible and effective innovations for the research themes: Humans and Technology, Supply Chain Management, Sustainability and Circularity, and Value of Data-Driven Intelligence.

Job Description

Companies are increasingly using data to make decisions, also in the context of maintenance optimization. Data can help answer critical questions: When should maintenance be performed, what maintenance actions should be performed, or when to supply spare parts? However, not all relevant information is covered by the available data. For example, an upcoming period in which machinery will be used more intensively, or an interaction effect with another machine that is getting faulty. Furthermore, a well designed machine doesn’t fail too often, so it takes time before one can base predictions on data coming from this machine, and human knowledge may be required to judge which other machines may experience similar failure behavior. Therefore, in the foreseeable future, human knowledge and human judgement will remain of key importance.

We are collaborating in the project RAMSES with multiple organizations active in the area of maintenance. Our aim is to optimize maintenance planning, through the use of data and human judgement. That means that we want to determine when to involve humans in the decision-making process, and when not, how to integrate the human judgement, and how to present information to human decision-makers in such a way that they can understand the information and add their judgement. There is plenty of opportunity for rigorous, theoretically founded research with actual data from and implementation in practice, thus having impact both in academia and industry. Although we are certainly open to publishing a paper in a top AI conference, our primary outlet are (top) journals in the field of management science and operations research. For an impression of the type of research we perform, please have a look at the following papers: 

  • Imdahl, C., Hoberg, K., & Schmidt, W. (2021). Targeted automation of order decisions using machine learning. Available at SSRN 3822131. https://doi.org/10.2139/ssrn.4292438.
  • Khosrowabadi, N., Hoberg, K., & Imdahl, C. (2022). Evaluating human behaviour in response to AI recommendations for judgemental forecasting. European Journal of Operational Research303(3), 1151-1167. https://doi.org/10.1016/j.ejor.2022.03.017.
  • Van der Staak, B., Basten, R., van de Calseyde, P., Demerouti, E., & de Kok, T. (2024). Light-touch forecasting: A novel method to combine human judgment with statistical algorithms. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2024.04.003.
  • Akkermans, H., Basten, R., Zhu, Q., & Van Wassenhove, L. (2024). Transition paths for condition‐based maintenance‐driven smart services. Journal of Operations Management, 70(4), 548-567. https://doi.org/10.1002/joom.1295.

Start date: As soon as possible; 1 September 2025 the latest.

Job Requirements

  • A Master's degree in Operations Research, Econometrics, Industrial Engineering, (Applied) Mathematics, or a related field.
  • Strong analytical and mathematical skills and demonstrated competence for data-driven research.
  • An interest in human behavior, ideally knowledge on behavioral operations management, human-technology interaction, or a related field.
  • The ability to work on a challenging topic that has both fundamental and applied research aspects.
  • Proven excellent verbal and written communication skills, including proficiency in English and an ability to collaborate in an international setting.
  • Motivation to develop teaching skills and coach students.

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 assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
  • 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. € 2,901 max. € 3,707).  
  • 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. 

Information

Do you recognize yourself in this profile and would you like to know more? Please contact dr. Christina Imdahl ([email protected]) or dr. Rob Basten ([email protected]).

Visit our website for more information about the application process or the conditions of employment. You can also contact Jolanda van der Sande, HR Advisor, [email protected] or +31 40 2474465. 

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

  • Cover letter in which you describe your motivation and qualifications for the position.
  • Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

 

Type of employment: Temporary position
Contract type: Full time
Salary: Scale P
Number of positions: 1
Full-time equivalent: 1.0 FTE
City: Eindhoven
County: Noord-Brabant
Country: Netherlands
Reference number: 2025/92
Published: 2025-04-01
Last application date: 2025-05-04

Arbeidsoppgaver

Tittel
PhD in judgmental decision making: Combining data and human judgment
Plassering
De Zaale Eindhoven, Nederland
Publiseringsdato
2025-04-01
Søknadsfrist
2025-05-04 23:59 (Europe/Amsterdam)
2025-05-04 23:59 (CET)
Jobbtype
Lagre jobben

Flere jobber fra denne arbeidsgiveren

Viser jobber på Engelsk, Svensk, Norsk, Dansk Endre innstillinger

Om arbeidsgiveren

We are an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude.

Besøk arbeidsgiverens side

Interessante artikler