Postdoc Risk-aware Autonomous Navigation

Postdoc Risk-aware Autonomous Navigation

Published Deadline Location
23 Feb tomorrow Delft
You will investigate methods for risk-aware navigation among decision-making agents, using learning and optimization, and apply them to self-driving cars and teams for quadrotors.

Job description

While automation offers opportunities to make society safer, it comes with new risks, some of which are fundamental and, others more technological. Autonomous agents require an understanding of how humans respond to the uncertainty and risk that they bring. From the agent’s perspective, actions are taken to bring itself into safety if there are uncertainties, but this may introduce new risks for others. For example, a vehicle that comes to a stand- still at a strange location, or reduces speed for a green traffic light, has already resulted in accidents, simply because this does not match human expectations. It is a major challenge to develop agents and frameworks that account for uncertainty, risk and interaction in the way humans do.

As human behavior depends on a tightly controlled perception-action cycle that carefully considers uncertainty and risk, so should the behavior of an autonomous agent. But this is not trivial to attain. For example, the dynamics of the environment in which it operates can be unpredictable, and control options may be unavailable or have limited ability. Inspired by how human brains deal with uncertainty, in this project you will develop probabilistic frameworks for motion planning in autonomous agents, such as cars or teams of drones. We will work on a fundamental understanding of how autonomous agents can cope with uncertainty and provide means for computing performance guarantees of autonomous AI agents under uncertainty, which will be integrated to various degrees into a use-case with self-driving shuttles.

Based on your experience and interests, you can focus on learning for planning, risk-aware motion planning under uncertainty, learning of interaction models, multi-robot learning, multi-modal prediction models, or other related topics to this project. You will work closely together with two PhD students, one focusing on motion planning and one focusing on trajectory prediction. You will also coordinate our efforts towards a demonstrator with a self-driving vehicle and interact with the consortium.

You will work on the NWO-NWA project "Acting under Uncertainty", which is formed by a consortium of several Dutch universities and companies, 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: https://www.autonomousrobots.nl/

The main focus of the Cognitive Robotics department is the development of intelligent robots and vehicles that will advance mobility, productivity and quality of life. Our mission is to bring robotic solutions to human-inhabited environments, focusing on research in the areas of machine perception, motion planning and control, machine learning, automatic control and physical interaction of intelligent machines with humans. We combine fundamental research with work on physical demonstrators in areas such as self-driving vehicles, collaborative industrial robots, mobile manipulators and haptic interfaces. Strong collaborations exist with cross-faculty institutes TU Delft Robotics Institute and TU Delft Transport Institute), our national robotic ecosystem (RoboValley, Holland Robotics) and international industry and academia. http://www.cor.tudelft.nl/

Specifications

Delft University of Technology (TU Delft)

Requirements

The candidate has, or is about to complete, a PhD degree in Robotics, Systems and Control, Computer Science, Applied Mathematics, or a related field. The candidate must be able to work at the intersection of several research domains 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 of foremost importance. Excellent command of the English language is required, as well as excellent communication skills. Candidates with a background in motion planning, control theory, machine learning or robotics are especially encouraged to apply. Experience with reinforcement learning algorithms is a strong plus.

Conditions of employment

Fixed-term contract: 24 months.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: € 4.036 - € 5.090 per month gross). The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

This position is a temporary assignment for 24 months.

Employer

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!

Department

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.

Additional information

For more information about this vacancy, please contact Associate Professor Dr. Javier Alonso-Mora (j.alonsomora@tudelft.nl).

Are you interested in this vacancy? Please apply before 17 April 2024 via the application button and upload:

  1. a letter of motivation explaining why you are the right candidate for this project;
  2. (max) one page research statement highlighting your research skills for this position (you may comment on your past projects) and what you would like to work on in the Postdoc (you may combine this with your motivation letter);
  3. an updated cv;
  4. list of your publications (may also include publications under review);
  5. your most relevant scientific publication (or a link to download it);
  6. a link to your PhD thesis, or draft, if available;
  7. email addresses of (at least) two referees;
  8. exam transcripts from your Master (optional).

Applications may be reviewed continuously as they are received.

The starting date is flexible within 2024.

Notes
- You can apply online. We will not process applications sent by email and/or post.
- Please do not contact us for unsolicited services.

Specifications

  • Postdoc
  • Engineering
  • 36—40 hours per week
  • Doctorate
  • TUD05062

Employer

Delft University of Technology (TU Delft)

Learn more about this employer

Location

Mekelweg 2, 2628 CD, Delft

View on Google Maps

Interesting for you

X

Apply for this job

Apply for this job

This application process is managed by the employer (Delft University of Technology (TU Delft)). Please contact the employer for questions regarding your application.

Thank you for applying

Please contact the employer for questions regarding your application.

Tip: save this job as favorite in your AcademicTransfer account. This gives you an immediate overview and makes it easy to find the job later on. No account yet? Create it now and take advantage of other useful functionalities too!

Application procedure

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

Application procedure

Application procedure

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

Make sure to apply no later than 17 Apr 2024 23:59 (Europe/Amsterdam).