Research scientist in AI for Robotics F/M
The Spatial AI team at NAVER LABS Europe conducts research on AI for robotics and spatially aware agents. Our work is motivated by challenging real-world robotics problems and we are currently building the next generation of agents capable of robust high-level reasoning in complex real-world environments.
One of the team’s research directions focuses on AI for manipulation and mobile manipulation. We develop systems that learn through interaction, acquiring diverse, whole-body, contact-rich skills to tackle complex long-horizon tasks. We combine a passion for robotics and its unique problems with an understanding of (and experience in) large-scale machine learning, deep learning and generalization.
Through close collaborations with computer vision and robotics teams across NAVER LABS, researchers have the opportunity to connect fundamental research questions with real operational problems. This creates a unique environment to pursue ambitious research directions, publish in leading conferences, and contribute to emerging AI-driven robotics services.
The position
We encourage early‑career researchers and recent PhD graduates to apply.
Responsibilities
- Conduct research on machine learning approaches for robotics.
- Develop new models and algorithms in robotics, perception (computer vision) and sequential decision taking.
- Design and implement prototypes and proof‑of‑concept systems to evaluate new ideas and algorithmic approaches.
- Run and analyze large‑scale experiments both in simulation and on real robotics platforms with a hands‑on approach.
- Contribute to publications in leading conferences and journals in machine learning, artificial intelligence, computer vision and robotics.
Required qualifications
- PhD in machine learning, robotics, computer vision, or a related field.
- Strong background in machine learning and AI for robotics.
- Excellent programming skills in Python and experience with deep learning frameworks such as PyTorch.
- Experience in designing, implementing, and evaluating machine learning models, especially policies for robotics tasks (manipulation, navigation, mobile manipulation, etc.).
- Experience with large‑scale experiments, simulation environments, or real‑world robotics environments.
- Strong interest in research problems and, importantly, their application to real life industrial scenarios.
- Ability to work collaboratively in multidisciplinary research environments.
- Publications in leading conferences in machine learning, artificial intelligence, computer vision or robotics (e.g., NeurIPS, ICLR, ICML, CVPR, ICCV/ECCV, IROS, ICRA).
Preferred qualifications
- Experience with deep reinforcement learning.
- A solid background in the fundamentals of robotics (e.g. kinematics and dynamics, control, path planning and physics simulation).