Do you want to develop human-centred RL algorithms to shape the liveable cities of tomorrow?
Human-centred AI techniques, such as Reinforcement Learning from Human Feedback (RLHF), hold great potential for supporting design methodologies in urban planning. This PostDoc position focuses on AI-based recommender systems to guide stakeholders in choosing a mobility system design. Specifically, the research builds on RLHF techniques, considering algorithmic challenges such as multiple objectives, the robustness of designs and the transparency of the design recommendation process.
The position is offered in the context of the Mobility DesAIgn Lab, a project that investigates how digital twins can be used responsibly for design issues in the field of mobility, transport and logistics in cities. The PostDoc will be embedded in the Sequential Decision Making group within TU Delft’s Intelligent Systems department, with close collaborations with project partners TNO and TU Delft’s Transport & Planning department. More information on the project (and a 2nd PostDoc vacancy within the project) can be found at its website: [see original application].
Job requirements
The candidate should have:
• a PhD degree in Artificial Intelligence (AI) or closely related topics in computer science, mathematics, or physics,
• a thorough understanding of reinforcement learning,
• fluency in English.
The ideal candidate:
• is interested in working in a multi-disciplinary project also involving transport engineering and societal partners,
• is a strong communicator and can work well in a team,
• is self-motivated to do cutting-edge research.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact!
Faculty of Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment. Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Conditions of employment
• Duration of contract is 2 years Temporary
• A job of 36-40 hours per week.
• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.
Will you need to relocate to the Netherlands for this job?
TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.
Additional information
If you would like more information about this vacancy or the selection procedure, please contact [see original application].
Application procedure
Are you interested in this vacancy? Please apply no later than 30 January 2026 via the application button and upload the following documents:
• CV
• Motivational letter
You can address your application to [see original application].
Please note:
• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.

Postdoc Reinforcement Learning from Human Feedback applied to Mobility System Design

TU Delft