Meta AR/VR Job | Research Scientist Intern, Machine-Learning & Physics (PhD)
Job（岗位）: Research Scientist Intern, Machine-Learning & Physics (PhD)
Type（岗位类型）: Machine Learning | Research
Citys（岗位城市）: Redmond, WA
Date（发布日期）: Before 2021-12-14
Summary（岗位介绍）
The Meta Reality Labs (RL) is committed to doing its part by developing technology and shipping the products that are necessary to make AR/VR compelling, pervasive and universal. As a PhD intern at FRL, you will be researching and developing, state-of-the-art, physics-inspired, machine learning technologies. The ideal candidate is pursuing a PhD with a strong background in machine learning, deep learning, 3D data processing (ideally through deep neural networks) and physics inspired neural networks. You should be able to take a real-world problem and develop physics-inspired machine learning methods to model real-world object interactions to estimate the final configuration, forces/pressure and the impact of different material properties. It’s expected that the candidate has solid hands-on experience with training large-scale ML models on cloud compute infrastructure. The candidate should also excel at working in a dynamic cross-functional environment with great communication skills.
Our internships are twelve (12) to sixteen (16) weeks long and we have various start dates throughout the year.
Qualifications（岗位要求）
Currently in the process of obtaining a Ph.D. degree in the field of Computer Science, Machine-Learning, Computer Vision/Graphics, Computational Physics/Mechanics/Aerospace or similar field
3+ years of experience, including PhD research, working in machine learning, computer vision, 3D/mesh/point-cloud processing using neural networks
Experience with C++ or Python
Hands-on experience with open-source deep-learning frameworks such as PyTorch, TensorFlow, MxNet
Interpersonal experience: cross-group and cross-culture collaboration
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
Description（岗位职责）
Advance the state-of-the-art in machine learning towards modeling physical phenomenon ie contact models using learning approach.
Build advanced physics-based neural-networks involving complex geometries.
Effectively collaborate across cross-functional teams to define functional requirements and drive deployment.
Implement the system learning framework in PyTorch.
Present regularly to large cross-functional teams and communicate progress.
Engage the wider academic community to pursue research in this direction through publications and/or workshop/challenge/tutorial organization top-tier conferences
Additional Requirements（额外要求）
Experience working on novel machine-learning problems exhibited in the form of publications in top-tier conferences/journals such as NeurIPS, CVPR, SIGGRAPH and similar venues
Intent to return to degree-program after the completion of the internship
Research experience in physics-informed neural networks
Experience with biomechanical modeling & simulations, computational mechanics, advanced optimization techniques
Experience with commercial finite-element simulation tools (ANSYS, Abaqus, etc) or open-source packages
Experience with automation, robotics, sensors, 3D computer vision is an added bonus
