Postdoc in Reinforcement Learning for Stochastic Optimization

Do you have an inquisitive mind and a passion for applied mathematics? Vrije Universiteit Amsterdam invites you to apply for a two-year postdoctoral position in Reinforcement Learning for Stochastic Optimization.

Postdoc in Reinforcement Learning for Stochastic Optimization

Your function

The Department of Mathematics of Vrije Universiteit Amsterdam welcomes applications for a two-year Postdoctoral position in Reinforcement Learning for Stochastic Optimization. The candidate is expected to conduct high-quality research at the intersection of reinforcement learning and stochastic optimization. The objective is to contribute to the development of novel methodologies that advance both theoretical understanding and practical application. The postdoc will actively explore how reinforcement learning techniques can be applied across a range of complex operational domains, such as energy systems, health care, and scheduling and planning. A strong interest in interdisciplinary collaboration and the ability to connect with ongoing departmental research efforts are essential. Preference will be given to candidates who can connect to existing research strengths in the department.

The preferred starting date is 01.09.2026

Your duties

• conducting research in the area of Reinforcement Learning (85%)
• contributing to the teaching portfolio of the Department of Mathematics (15%)
• conducting high-quality research at the intersection of reinforcement learning and stochastic optimization
• developing novel methodologies that advance both theoretical insights and practical applications
• collaborating across disciplines and contribute to ongoing research activities within the department
• applying reinforcement learning techniques to a variety of operational domains, including energy systems, health care, and telecommunication systems

Your profile

• a PhD in mathematics, operations research or computer science
• a strong background in Reinforcement Learning
• demonstrated programming skills
• strong independent research skills
• ability to work independently and in a collaborative, interdisciplinary environment
• team spirit and good communication skills in English

What do we offer?

A rewarding position in a socially involved organization. On a full-time basis, the remuneration amounts to a minimum gross monthly salary of €4,412 and a maximum of €5,538. The job profile is based on the university job ranking system and is vacant for 0.8-1.0 FTE.

The appointment will initially be for 2 years. Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:

• 8% holiday allowance and 8.3% end-of-year bonus
• contribution to commuting expenses
• optional model for designing a personalized benefits package
• a maximum of 41 days of annual leave based on full-time employment
• good paid parental leave scheme

About us

The VU Analytics and Optimization Group

The Analytics & Optimization group at Vrije Universiteit has many national and international connections, and is internationally leading in the field of analytics and optimization. We form a very active and collaborative group and are fascinated by mathematics for business applications. We are specialized in stochastic processes such as queueing systems and their controlled counterpart, Markov decision processes. We also cover related fields such as simulation, machine learning and statistics, because you have to combine them in the analytical process.

The Department of Mathematics

The Department of Mathematics strives for excellence in research. The department balances pure mathematical research with mathematical research motivated by applications. Researchers in the department are on the one hand active at a fundamental and theoretical level, and, on the other hand, work on applications with links to business, the sciences, and societal issues. The department has a strong international research staff with expertise in dynamical systems, topology, geometry and algebra, as well as in stochastics (statistics, data analytics, probability).