PhD Internship - Remote
Job Summary
Job Description
Meshcapade is offering a PhD Internship focused on advancing humanoid motion tracking in physical simulation. The role centers on developing cross-embodiment body and hand motion tracking algorithms that enable humanoid robots to precisely follow human motion while maintaining balance across diverse terrains.
Responsibilities:
- Design and implement workflows to transfer motions from SMPL-X models to humanoid robots in simulation environments.
- Develop and refine algorithms for cross-embodiment motion tracking.
- Evaluate and benchmark tracking performance under various physical constraints.
- Integrate generative motion models, such as diffusion models, into tracking pipelines.
- Conduct experiments and document findings for potential academic publication.
- Collaborate with research teams across academic and industry contexts.
Requirements:
- Strong knowledge of PyTorch, deep learning, neural networks, and C++.
- Experience with reinforcement learning and robot physical simulation.
- Familiarity with SMPL, SMPL-X, or character animation frameworks.
- Solid software engineering practices including version control and documentation.
- At least one publication in top-tier conferences such as CVPR, ICCV, ECCV, IROS, or ICRA.
- Ability to work independently in a remote research environment.
Benefits:
- Research experience spanning academia and industry.
- Opportunity for paper publication.
- Six-month contract with flexible remote work.
- Inclusive and diversity-focused company culture.
This internship provides an opportunity to contribute to foundational research in humanoid robotics and intelligent motion modeling.
