PhD Position Novel View Synthesis

Neural Radiance Fields (NeRFs) and Gaussian Splatting have revolutionized 3D scene reconstruction and novel view synthesis, enabling real-time, high-fidelity rendering of a scene from an arbitrary viewpoint, enabling the manipulation of the scene. In our previous work, Neuro NCAP, we used these techniques to create crash test simulators for autonomous vehicles that can simulate actions in closed-loop by synthesizing novel viewpoints of the ego vehicle. Building on these breakthroughs, this PhD project at TU Delft explores AI-driven methods to enhance closed-loop simulation for safety-critical scenarios. A key focus is developing learned simulators that generate radar and lidar data from camera sensors. Additionally, the research will investigate end-to-end prediction and planning approaches that integrate radar-based perception and are trained in closed-loop, moving beyond traditional modular robotics pipelines to create more robust and scalable autonomous systems.

This fully funded, four-year PhD position at the Intelligent Vehicles Section of TU Delft. The research is part of the EU Horizon MOSAIC project and is conducted in partnership with NXP, a leading chip manufacturer. 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 primary supervisor will be Dr. Holger Caesar.

• We are seeking PhD applicants with an interest in performing cutting edge research in an active and exciting research area.
• Prior experience working with Neural Radiance Fields or Gaussian Splatting.
• Prospective applicants should have a strong academic record with a solid background in Machine Learning (Deep Learning, generative models, diffusion models).
• Knowledge in sensor data processing and radaris a plus.
• Good programming skills (Python) and knowledge of deep-learning frameworks (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.
• The work takes place in Delft, The Netherlands, but allows for working two days per week from home.

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! 

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. 

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. 

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. 

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2872 per month in the first year to € 3670 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. 

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.  

Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

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13 April 2025 via the application button and upload the following documents:

• CV

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. 

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.