Autonomous vehicles have been shown to underperform when deployed on conditions that differ substantially from the training conditions, so-called domain gaps. These domain gaps can include deployment in different regions, weather or using different sensors. Numerous domain adaptation methods have been proposed to bridge these domain gaps and let the model operate well on the target data. In this project we seek to find an intermediate representation for data coming from varied sources. By bringing new data into this representation, we overcome domain gaps and are able to train models that are robust to different conditions, also referred to as foundation models. While foundation models have achieved widespread success on images and text, currently none exist for radar data, making this a promising research direction. These foundation models will bring superior performance and allow us to utilize data from varied sources, thus reducing the data collection and labeling costs.

The Intelligent Vehicles section at TU Delft, the Netherlands, invites applications for a fully funded two-year (up to 30 months) Post-Doctoral research position in the area of foundation models for autonomous vehicles. This position is part of the EU Horizon project Cynergie4MIE and in collaboration with the chip company NXP. While the exact task (detection, segmentation) is flexible, it should make use of radar sensors, potentially fused with other sensors. Your results will be published in top tier conferences like CVPR, ICCV, ECCV, ICRA and NeurIPS. For your work you will have access to the compute resources of TU Delft, ranging from personal machines, to shared GPU servers, the Delft AI Cluster that is shared across departments, as well as DelftBlue, which is one of the top 250 supercomputers in the world. Your main supervisor will be Dr. Holger Caesar, creator of the nuScenes dataset and co-author of the PointPillars method for lidar-based object detection. You will receive hands-on mentoring for your career development and help with applying for future research grants, to kick-start your continued academic career.

• We are seeking Post-Doc applicants with an interest in performing cutting edge research in an active and exciting research area.
• Prospective applicants should have a strong academic record with a solid background in sensor processing (vision/radar/lidar, sensor fusion) and Machine Learning (Deep Learning, domain adaptation, foundation models).
• Good programming skills (Python/Matlab) and knowledge of deep-learning frameworks (TensorFlow/PyTorch) are expected.
• A certain affinity towards turning complex concepts into real-world practice (i.e. vehicle demonstrator) is desired.
• The successful candidate is expected to be able to act independently as well as to collaborate effectively with members of a larger team and supervise Master and PhD students. Good English skills are required.

Fixed-term contract: 1-2 years.

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.

From 1 September next, a salary increase of 3.7% applies due to a Collective Agreement amendment, followed by an additional 1% increase on 1 January 2025. In addition, most employees employed on 1 September 2024 will receive a one-off payment of €300 gross based on full-time employment.

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.

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.