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PhD Internship - Remote

Meshcapade

Role overview

Qualifications

  • 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
  • At least one paper in CVPR/ICCV/ECCV/IROS/ICRA or equivalent

Responsibilities

  • Creating a workflow to transfer motions from SMPL-X to humanoids in simulation
  • Developing an algorithm to perform cross-embodiment motion tracking
  • Evaluating the performance of the tracking algorithm
  • Combining generating motion models to the tracking algorithm

About the company

Meshcapade logo

Meshcapade

Artificial Intelligence & Machine Learning Services

Meshcapade is the digital human company. We are building foundation models & 3D generative models to bring digital humans to life. Try out our platform: meshcapade.meJoin us! meshcapade.com/careersMeshcapade is a startup based in Tübingen, Germany, specializing in AI solutions for modeling, analysis and synthesis of 3D digital humans in motion. It was founded in 2018 by Naureen Mahmood, Talha Zaman and Michael J. Black as a spin-off of the Max-Planck Institute for Intelligent Systems.Since then it has become the trusted supplier for 3D human technology for over 100 customers in apparel, fitness, synthetic data, AR/VR, telepresence and entertainment, including 7 out of the top 10 NASDAQ companies.

Company details

Company typeStartup
IndustryArtificial Intelligence & Machine Learning Services
Company size11 - 50

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Job description

Who are we?

To create an intelligent humanoid in the 3D world, the first step is to track real human motions in physical simulation. Although human motion capture and generation have been extensively studied in the past, it is still unclear how to let a humanoid track human motions precisely, while keeping the body balance at various terrains. Our goal is to explore this direction, and develop an effective cross-embodiment body and hand motion tracking algorithm in physical simulation.

What you will be doing

  • 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.

Who you are

  • 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.

What we offer

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

Our values

Diversity isn’t just a statement at Meshcapade, it sits at the core of the company.

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.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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