1. Vacatures
  2. Technische Universiteit Delft (TUD)
  3. PhD: Pedestrian/Cyclist Motion Prediction for Self-Driving Vehicles

Helaas, deze vacature staat inmiddels niet meer online

Kijk gerust verder naar andere vacatures.

PhD: Pedestrian/Cyclist Motion Prediction for Self-Driving Vehicles

The Intelligent Vehicles group at TU Delft (www.intelligent-vehicles.org) is seeking a PhD candidate with an interest in performing cutting edge research in …

bijna 2 jaar geleden


Mekelweg, Delft, Zuid-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 - 40 uur
€ 2266 - € 2897 per maand


The Intelligent Vehicles group at TU Delft (www.intelligent-vehicles.org) is seeking a PhD candidate with an interest in performing cutting edge research in the area of self-driving vehicles. This PhD position is part of the project “Safe interaction of automated vehicles with vulnerable road users” (SafeVRU). The project will develop sensing, intent recognition, and vehicle control strategies for the interaction of automated vehicles with vulnerable road users (VRU) such as pedestrians and cyclists. Several Dutch industry partners participate in this project (2getthere, TNO Automotive, NXP); beyond these, multiple collaborations with the European automotive industry exist.

The PhD position involves developing motion/behavior models for pedestrians/cyclists, that can accurately predict their future trajectories. These models are to be learned/parametrized using training data and will take into account sensor measurements (e.g. position, velocity, pose, gestures, and traffic environment) and prior knowledge (physical constraints, map data). A challenge is to deal with the uncertainty derived from imprecise sensor measurements and from highly maneuverable targets that can change their velocities abruptly (e.g. change of direction, start/stop walking). Several motion model types will be considered initially, based on explicit dynamics, trajectory learning and planning (agents). In particular, deep learning for motion prediction will be investigated.


Applicants should have a strong academic record with a solid background in computation, sensor processing (e.g. computer vision), machine learning and AI. Good programming skills are expected, preferably in C++ and MATLAB/Python. Knowledge of deep-learning frameworks (TensorFlow/Torch/Caffe) and OpenCV/ROS/CUDA is a plus. A certain affinity towards turning complex concepts into real-world practice (i.e. vehicle demonstrator) is desired. Applicant(s) are expected to be able to act independently as well as to collaborate effectively with members of a larger team. Good English skills are required.


TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information

Additional information

For more information about this position, please contact Prof.dr. D.M. Gavrila, e-mail: D.M.Gavrila@tudelft.nl .

To apply, please submit:

  • a letter of motivation explaining why you are the right candidate,
  • a detailed CV,
  • a complete record of Bachelor and Master courses (including grades),
  • a link to your Master’s Thesis (at least as draft),
  • any publications, and a list of projects you have worked on with brief descriptions of your contributions (max 2 pages), and
  • the names and contact addresses of two references.

All these items should be combined in one PDF document. Applications should be submitted as soon as possible by email to Application-3mE@tudelft.nl. When applying for this position, please refer to vacancy number 3mE18-55 in the subject of the email.