In short

ORTEC helps many of the world's best-run organizations make better data-driven decisions. Our decision support software and data science expertise enable you to improve your business results and make a positive impact on the world.
Many businesses deal with fluctuating workloads, due to e.g. seasonal/weekly patterns or various disruptions. And many of those workloads have a time interval during which they have to be executed, but no fixed starting time. Determining those starting times has a direct effect on the number of employees that must be scheduled at any given time. With workforce being increasingly scarce, it is vital to make efficient use of workforce by scheduling employees at the right time (and the right place). Furthermore, it is important to acknowledge that employees have more influence than ever on their schedules (e.g. days on / off requests, working time preferences). Additionally, adherence to complex labor rules (e.g. enough daily/weekly rest) is imperative. Consequently, creating an employee schedule from scratch, with the objective of optimizing employee utilization, presents a significant challenge for planners.
This research investigates how task planning can help in creating a more stable workload (peaks less high and holes less deep), such that shift creation can result in less over- and/or understaffing overall. Those shifts will later be the input for the rostering problem where available employees need to be assigned to the duty demands.
What can you expect to do?
• Review existing literature and methodologies related to shift creation, task scheduling and integrated problems.
• Familiarize yourself with the existing dataset
• Create a new model and a new algorithm for this duty demand creation problem
• Evaluate the impact on the algorithm based on the solution, runtime etc.
• You are currently living in the Netherlands, studying at a Dutch University, and communicate fluently in Dutch or English, verbally and in writing.
• You are a master student in Operations Research, Econometrics, Applied Mathematics or another related field and looking for a graduation project.
• You like programming and can hunt for bugs.
• You have experience with heuristics.
• You are available for a minimum of six months to a maximum of nine months, ideally starting in February or March 2026.
• You can travel to the office (in Zoetermeer) at least twice a week
• Entrance to the most passionate powerhouse in applied mathematics. We share a drive to use our problem-solving skills to improve our planet, from the world at large to our own backyard.
• Inclusion in a company founded by graduate students back in 1981, which today still fosters its students by:
o Excellent supervision during your graduation project,
o Good internship allowance, laptop, and other office facilities,
o An open, kind, and fun culture.
o Access to Young ORTEC formal and informal events
The next steps:
If you're an enthusiastic graduate student seeking a hands-on experience that combines analytical thinking, multidisciplinary collaboration, and problem-solving, we invite you to join us on this exciting assignment by uploading your CV, motivation letter and grade lists (BSc and MSc in PDF if applicable) by the 1th of January 2026. The recruitment process will consist of two online assessments and an interview.
We will help you to thrive in your field of expertise. We offer development programs, tailored to your individual needs and function requirements, including opportunities to attend courses and seminars. We offer challenging, practical hands-on experience with opportunities to work abroad. We operate in a flat organizational structure that keeps communication lines short. The atmosphere is open, informal, cooperative and positive. We employ over 1000 people in the Netherlands (HQ), Belgium, Germany, France, the U.K., Romania, Italy, the U.S., Australia, Brazil, Poland, Denmark and Singapore. Visit our website ortec.com to learn more about our solutions and clients’ experiences. Please do not use this vacancy as an acquisition opportunity.