Delft University of Technology
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PhD Position in Foundation Models for Automotive Imaging Radar at TU Delft Delft University of Technology in Netherlands
Degree Level
PhD
Field of study
Computer Science
Funding
Doctoral candidates are offered a 4-year employment period in principle, split into an initial 1.5-year contract and a subsequent 2.5-year contract subject to a positive progress assessment. Salary ranges from €3204 to €4051 gross per month over the four years for a full-time 38-hour contract, plus 8% holiday allowance and an 8.3% end-of-year bonus. TU Delft also mentions a customizable compensation package, health insurance discounts, and a monthly work costs contribution.
Deadline
Oct 18, 2026
Country
Netherlands
University
Delft University of Technology

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About this position
PhD position at Delft University of Technology (TU Delft) in the Netherlands on foundation models for automotive imaging radar. The project sits in the Intelligent Vehicles group within the Department of Cognitive Robotics and is carried out in collaboration with Perciv.AI and NXP Semiconductors as an industrial partner.
The research focuses on learning general radar representations from largely unlabeled data, adapting them to downstream perception tasks with limited labels, and transferring ideas from vision and LiDAR foundation models to radar. Possible directions include multimodal foundation models, generalization across radar configurations, and generative or predictive modeling of dynamic radar scenes. The work combines methodological machine learning with experiments on real automotive sensor data and access to research vehicles, advanced radar prototypes, GPU servers, the Delft AI Cluster, and the DelftBlue supercomputer.
Study fields / keywords: machine learning, deep learning, foundation models, self-supervised learning, multimodal learning, 3D perception, radar, sensor fusion, computer vision, autonomous driving, robotics, electrical engineering, computer science.
Eligibility highlights: MSc in Computer Science, Artificial Intelligence, Robotics, Electrical Engineering, or a closely related field; strong academic record; Python/PyTorch experience preferred; good English; experience with radar, signal processing, computer vision, autonomous driving, or sensor fusion is advantageous.
Funding and contract: 4-year PhD employment in principle, with salary from €3204 to €4051 gross per month, plus holiday allowance and end-of-year bonus. TU Delft also mentions health insurance discounts and a work costs contribution.
Application window: apply by 18 October 2026 via the online application button. Upload a motivation letter, CV, BS/MS transcripts, and supporting materials such as thesis drafts, publications, project descriptions, or code repositories.
Supervisors: Prof. Dariu Gavrila and Dr. Julian Kooij.
Funding details
Doctoral candidates are offered a 4-year employment period in principle, split into an initial 1.5-year contract and a subsequent 2.5-year contract subject to a positive progress assessment. Salary ranges from €3204 to €4051 gross per month over the four years for a full-time 38-hour contract, plus 8% holiday allowance and an 8.3% end-of-year bonus. TU Delft also mentions a customizable compensation package, health insurance discounts, and a monthly work costs contribution.
What's required
Applicants should have an MSc degree in Computer Science, Artificial Intelligence, Robotics, Electrical Engineering, or a closely related field. A strong academic record and solid background in machine learning and deep learning are required. Candidates should be able to develop, understand, and critically evaluate machine learning research software, preferably in Python and PyTorch. Interest in foundation models, self-supervised learning, multimodal learning, and 3D perception is expected. An affinity for translating methodological research into experiments with real automotive sensor data and vehicle demonstrators is important. Good written and spoken English is required. Experience with radar, signal processing, computer vision, autonomous driving, or sensor fusion is advantageous.
How to apply
Apply online via the application button on AcademicTransfer before 18 October 2026. Upload a motivation letter, detailed CV, BS and MS transcripts, and any supporting materials such as thesis drafts, publications, project descriptions, or code repositories. Do not send applications by email or post.
More information can be found here
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