Resume Score

Check how well your resume matches this job before you apply.

Sign in to check score

About the role

  • PhD Internship focused on developing cross-embodiment body and hand motion tracking algorithms for humanoids. Engaging in research experiences and possible publication opportunities.

Responsibilities

  • 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.

Requirements

  • 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.

Benefits

  • Research experiences both in academia and industry.
  • Possibility of paper publication.
  • 6-months working contract.
  • Flexible remote work with global availability.

Job title

Job type

Internship

Experience level

Entry level

Salary

Not specified

Degree requirement

Postgraduate Degree

Tech skills

PyTorch

Location requirements

RemoteWorldwide

Report this job

Found something wrong with the page? Please let us know by submitting a report below.