NEW: PhD Position in real-time 3D view synthesis and scene representation using Neural Radiance Field models

Job description

Imec-IPI is looking for a qualified and motivated PhD student to work on Real-time 3D view synthesis methods and neural radiance field-based models. As a PhD student with IPI, you will be located at the TELIN offices at Campus UFO in Ghent. You will be offered an initial contract of 12 months, to be extended up to a period of 4 years in total with the aim of obtaining a PhD. The research will be partly fundamental (furthering the state of the art) and partly applied. You will collaborate with international industrial partners while embedded in a university research team that is internationally recognized for its extensive expertise regarding sensor fusion for autonomous driving, traffic monitoring and industrial safety.

The Image Processing and Interpretation (IPI) group at Ghent University-imec consists of +/- 40 experienced researchers, post-docs and professors. IPI conducts research in a wide array of both fundamental and applied image processing topics. Application domains of this research include intelligent & autonomous vehicles, surveillance and sensor networks, remote sensing, medical image analysis, video analysis and scene reconstruction.

Ghent University consistently ranks among the best 100 universities in the world, including, 69th by the Academic Ranking of World Universities (or Shanghai ranking) and 88th by U.S. News & World Report. The IPI Lab is location on the university’s UFO campus in the center of Ghent, Belgium, a city recently rated as one of the best places to visit in Europe for culture.

Candidate profile

You hold a Master of Science degree in computer science, electrical engineering or equivalent. You possess a strong knowledge of mathematics, probability theory, image processing, machine learning, and computer vision and are well versed in Python and/or C++. You have experience with original algorithm design that goes beyond the mere application of methods from literature.

You combine a strong interest in engineering and scientific research with a desire to see your work applied (in industrial, academic or (N)GO collaboration). You are able to learn quickly and independently. You aspire to become an expert in your field, while simultaneously collaborating with other researchers and senior staff to efficiently generate state-of-the-art results.

You are fluent in written and oral English and able to communicate your original ideas and results clearly and concisely. You are highly motivated to drive innovation in 3D scene representation methods and view synthesis methods to process 3D video content in real-time.


Neural Radiance Fields (NeRFs) represent a novel and very popular approach to 3D scene representation using neural networks. Instead of relying on traditional geometric primitives, NeRFs model a scene's volumetric density and view-dependent radiance functions directly. This allows for the generation of high-quality, novel views of a scene through rendering. NeRF methods have found applications in extended reality (AR, VR, MR) and computer graphics, offering a more accurate and flexible alternative to traditional 3D graphics techniques.

NERFs offer several advantages, such as detail and realism and the ability for novel view synthesis, but there are also several challenges, e.g., the computational cost, memory requirements and generalizability to dynamic scenes (with movements). For example, NERF methods are less suited when hundreds or thousands of views need to be generated in real-time to drive high-end display walls. NERFs also require a significant amount of training to achieve high-quality results.

You will be tasked with addressing the challenges associated with neural radiance fields, particularly in the context of real-time low latency rendering and view synthesis. The goal is to innovate and propose solutions that optimize the computational efficiency of NeRFs while maintaining or enhancing the visual quality of rendered scenes. This may involve algorithmic improvements, experimentation, and collaboration with industry partners to integrate these solutions into practical applications. The emphasis is on pushing the boundaries of 3D scene representation and rendering to contribute to the advancement of immersive visual experiences.

What we offer you

At IPI, we offer you the opportunity to conduct research in a highly international and friendly working environment. We provide ample opportunity for researchers to take initiative in their work and to develop their professional networks.

The salary is competitive and will be determined by the university salary scales. Staff members can count on a number of benefits, such as a broad range of training and educational opportunities, 36 days of vacation leave (on an annual basis for a full-time position), bicycle allowance, and more.

How to apply

Please submit your application by email to Prof. Bart Goossens with " [3DView] " in the subject line.

In your email, please include the following in 1 merged pdf file:

  • A cover letter with a brief motivation of your application: what do you consider the best aspects of your CV that demonstrate your academic excellence during your university education? What are your reasons for pursuing a PhD? Why would you like to work at UGent?

  • A detailed CV, describing your earlier experience and studies;

  • Contact details for three reference persons;

  • A list of publications (if available);

  • A transcript of your educational record (list of courses per year, number of obtained credits, obtained marks) if available. This need not be official documentation at this stage;

  • If available: 1-3 English language documents describing your earlier research or technical work (e.g., scientific papers, master thesis, report on project work, etc.). These documents need not be on the topic of the advertised position.

Applications remain welcome until the position is filled.

Image Processing and Interpretation