Meta AR/VR Job | Research Scientist Intern, Machine Learning for Human Cognition and Action (PhD)
Job（岗位）: Research Scientist Intern, Machine Learning for Human Cognition and Action (PhD)
Type（岗位类型）: Engineering
Citys（岗位城市）: Redmond, WA
Date（发布日期）: 2023-6-13
Summary（岗位介绍）
At Meta Reality Labs Research, we are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. The team brings together a world-class team of researchers, developers, and engineers to create the future of AR and VR, which together will become as universal and essential as smartphones and personal computers are today.
We are looking for a skilled and motivated research intern to join our team, whose mission is to apply sample-efficient machine learning methods problems in AR/VR input and interaction. Projects on our team span the space from cognitive modeling and human-in-the-loop experimentation as part of our platform AEPsych, (https://aepsych.org/), to supporting the design of novel sensors and tracking algorithms that can be used to understand humans and their behavior. In all cases we motivate our research via collaboration with domain experts, and contribute our unique focus on sample-efficiency, i.e. making our models work on small amounts of data collected from in-lab participants and / or one-off prototypes.
The chosen candidate will work with a diverse and highly interdisciplinary team of researchers and engineers and will have access to cutting edge technology, resources, and testing facilities.
Qualifications（岗位要求）
Currently has, or is in the process of obtaining a Ph.D degree in machine learning, artificial intelligence, statistics, data science, computational neuroscience, mathematical psychology, a related area, or equivalent work experience.
2+ years research experience in an area with potential applications to sample-efficient learning in the areas noted above. Example areas include active learning, deep Bayesian learning, Gaussian Process models, hierarchical / multitask / transfer learning, domain adaptation, or other relevant areas, as demonstrated via publications (conference or journal), open-source contributions, or similar venues.
1+ years of experience with SciPy/NumPy and at least one automatic differentiation framework (PyTorch, Tensorflow, JAX, Stan, etc) — PyTorch preferred.
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 (SOTA) in sample-efficient modeling for understanding human cognition and action writ large (e.g. tracking anything from cognitive effort to hand position).
Use our SOTA models to deliver advances in downstream experiments or demos – it has to work in real life. This is a challenge, but also an exciting opportunity to go beyond benchmarks and have other researchers and engineers directly benefit from your research.
Successful internships may also lead to publishable outcomes in top-tier journals or at leading international conferences.
Additional Requirements（额外要求）
Experience working directly with domain experts in non-ML fields, for example mechanical engineers or designers, neuroscientists, physicists, etc.
Experience writing research software used by others, for example as part of an academic collaboration, an open-source project, or equivalent.
Proven track record of achieving significant results as demonstrated by one or more grants, fellowships, patents, or first-authored publications at leading workshops or conferences such as NeurIPS, AAAI, ICML, AISTATS, UAI, IJCAI, or similar.
Intent to return to degree-program after the completion of the internship/co-op.
