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Post-doctoral Researcher (M/F) in Computer Vision
Job summary
A leading research organization in France is seeking a full-time researcher specializing in neural 3D reconstruction. The role involves integrating and optimizing advanced technology within open-source software. Candidates should have expertise in Computer Vision and programming skills in C++ and Python. This position offers opportunities for collaboration and innovation in a dynamic research environment.
Qualifications
- In-depth expertise in Computer Vision and Photogrammetry.
- Mastery of state-of-the-art Neural Rendering techniques.
- Advanced programming skills in C++ and Python.
Responsibilities
- Integrate, optimise, and stabilise neural 3D reconstruction methods.
- Develop mechanisms for outlier rejection.
- Adapt code to reduce computation times dramatically.
Skills
Education
Tools
Organisation/Company CNRS Department Institut de Recherche en Informatique de Toulouse Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage Researcher (R1) Country France Application Deadline 16 Dec 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
This position is part of the CNRS "OPEN" valorization project named DOPAMIn. It aims to transfer state‑of‑the‑art 3D reconstruction technology (RNb-NeuS), derived from academic research, into the open‑source industrial software AliceVision/Meshroom, in collaboration with the University of Zurich.
The researcher will integrate, optimise, and stabilise the RNb‑NeuS neural 3D reconstruction method within the AliceVision software architecture, enabling the creation of high‑precision digital twins.
- Implement processing nodes for normal field and intrinsic colour estimation.
- Integrate deep learning‑based methods (such as SDM‑UniPS or Uni‑MS‑PS).
- Develop the neural reconstruction node using photometric data as input.
- Ensure interfacing with the AliceVision library.
- Adapt the code to drastically reduce computation times (target: < 1 h).
- Replace proprietary dependencies (InstantNGP) with a flexible base (such as SuperNormal).
- Develop mechanisms for outlier rejection.
- Document the code for the open‑source community.
Full‑time work. Position based at the IRIT‑ENSEEIHT campus in Toulouse. Integrated within the REVA team at IRIT. Strong interaction with ALICIA‑Vision LabCom partners (CNRS / Technicolor‑Mikros).
- In‑depth expertise in Computer Vision and Photogrammetry.
- Mastery of state‑of‑the‑art Neural Rendering (NeRF, NeuS, SDF).
- Knowledge of Photometric Stereo methods.
- Advanced programming in C++ and Python.
- Mandatory mastery of GPU programming (CUDA) for optimisation.
- Experience with Deep Learning frameworks (PyTorch).
- Knowledge of the AliceVision architecture is a major asset.
- Autonomy and scientific rigour.
- Ability to work collaboratively (mixed academic/industrial context).
- Ability to meet short development deadlines (project mode).
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