About The Position

Meta Reality Labs Research is looking for an intern to help us develop the next-generation physics simulators for robotics applications. In particular, we are seeking candidates who have experience with physics simulations, computational mechanics, and robotics training, to devise algorithms that make simulation more effective in training control policies for dexterous robot manipulation. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Requirements

  • Currently is in the process of obtaining a PhD in computer science, computer graphics, computational mechanics, machine learning, computational mathematics or a relevant technical field
  • Research skills involving defining problems, exploring solutions, and analyzing and presenting results
  • Experience implementing numerical methods and/or deep learning models in a large-scale code
  • Proficient in C++ and/or Python
  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Nice To Haves

  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as SIGGRAPH, NeurIPS, ICML, ICLR, or similar
  • Experience with high performance/parallel computing (e.g. CUDA)
  • Experience with training deep learning models and familiarity with tools like PyTorch
  • Experience working and communicating cross functionally in a team environment
  • Intent to return to degree program after the completion of the internship/co-op
  • Availability for minimum 16 consecutive week internship

Responsibilities

  • Develop, implement, and test novel numerical methods for differentiable simulation of contact mechanics.
  • Develop and implement strategies for training dexterous robot manipulation policies that are efficient and robust under the complexity of contact.
  • Implement and optimize the methods devised in a larger software infrastructure, and collaborate with research scientists and software engineers to build demos and experiences based upon the developed tools.
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