Postdoc Reinforcement Learning from Human Feedback applied to Mobility System Design

This PostDoc position offers the opportunity to develop human-centred RL algorithms to help shape the liveable cities of tomorrow.

Job description

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.

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.

About TU Delft

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.

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. 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.

Conditions of employment

• Duration of contract is 2 years temporary.
• 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.
• Support for relocation to the Netherlands, including information and events to help you settle in Delft.
• A Dual Career Programme is available to support your accompanying partner with their job search in the Netherlands.

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel to help prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by candidates, 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.