- Creating a workflow to transfer motions from SMPL-X to humanoids (e.g. Unitree G1) in simulation.
- Developing an algorithm to perform cross-embodiment motion tracking.
- Evaluating the performance of the tracking algorithm.
- Combining generating motion models (e.g. diffusion models) to the tracking algorithm.
- Knowledge of PyTorch, deep learning, neural networks, C++.
- Knowledge of good software development practice, e.g. git, documentation.
- Knowledge of reinforcement learning and robot physical simulation.
- Knowledge of SMPL, SMPL-X, or character animation.
- At least one paper in CVPR/ICCV/ECCV/IROS/ICRA or equivalent.
- Research experiences both in academia and industry.
- Possibility of paper publication.
- 6-months working contract.
- Flexible remote work with global availability
We believe in the diversity of thought because we appreciate that this makes us stronger. Therefore, we encourage applications from everyone who can offer their unique experience to our collective achievements.
Germany only
