Postdoc Learning-based Multi-robot Mobile Manipulation in Human

Do you want to revolutionize the future of robotics by empowering mobile manipulators with intuition to seamlessly perform tasks alongside humans?

Job description

Mobile robots are not yet capable of seamless interaction in human populated environments, primarily due to the high complexity of modeling and reasoning over the effect that robot actions have on other robots and humans, and the inherent uncertainty. Humans rely on intuition, namely the ability to understand interaction instinctively, without the need for conscious reasoning. The goal of this project is to provide mobile robots with the ability to reason about their coordination with other agents and the associated risks, take appropriate actions and continuously reassess.

Your work can focus on any of the following:

Learning interaction models from humans, that we can then use as intuition for motion and task planners.

Advanced perception methods for dynamic environments.

Learning-based task and motion planning in human-centric environments.

You will work together with two PhD students, one focusing on motion planning and the other one focusing on task planning, and you will lead our efforts towards a demonstrator with multiple mobile manipulators and humans.

Thus, you will make a fundamental contribution towards intuitive multi-robot interaction, making it possible for teams of mobile robots to safely interact in human-centric environments and enabling a new level of automation in factories and cities.

You will work on the ERC Starting Grant project "Intuitive Interaction for Humans among Robots (INTERACT)" and be embedded within the Autonomous Multi-Robots Lab in the Department of Cognitive Robotics at TU Delft.

The goal of the Autonomous Multi-Robots Laboratory at the Delft University of Technology is to develop novel methods for navigation, motion planning, learning and control of autonomous mobile robots, with a special emphasis on multi-robot systems, on-demand transportation and robots that interact with other robots and humans in dynamic and uncertain environments. Building towards the smart cities of the future, our applications include self-driving vehicles, mobile manipulators, micro-aerial vehicles, last-mile logistics and ride-sharing. See:

Job requirements

The candidate has (or will soon have) a PhD degree in Robotics, Controls, Machine Learning, or a related field.

The candidate must be able to work at the intersection of several research domains, have a proven publication record, and have a passion for doing ground-breaking theoretical research and applying it to real robots.

Good programming skills and experience with programming languages such as Python and C++ are important.

Excellent command of the English language is required, as well as excellent communication skills.

Candidates with a background in machine learning for robotics are especially encouraged to apply.

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 Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

Click here to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.

Conditions of employment

Duration of contract is 2 years.

A job of 36-40 hours per week.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

The contract length is up to 2 years, depending on the start date. The preferred starting date is 1st September 2025. However, this is flexible and can be negotiated.

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

For more information about this vacancy, please contact Associate Professor Dr. Javier Alonso-Mora. Email: .

Application procedure

Are you interested in this vacancy? Please apply no later than 1 June 2025 via the application button and upload the following documents:

A letter of motivation explaining why you are the right candidate for this project. In your letter, highlight your research skills for this position (you may comment on your past projects) and what you would like to work on in the Postdoc.

An updated CV.

A list of your publications (may also include publications under review).

A link to your PhD thesis, or draft, if available.

Email addresses of (at least) two referees.

Grade transcipt from your Masters (optional).

You can address your application to Javier Alonso-Mora.

The review of applications will be continuous as applications are received. All applications up to the closing date will be considered.

Please note:

You can apply online. We will not process applications sent by email and/or post.

A pre-employment screening can be part of the selection procedure.

For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.

Please do not contact us for unsolicited services.