Meta AR/VR Job | Visiting Researcher, Methods/Models for Human Perception (PhD)
Job（岗位）: Visiting Researcher, Methods/Models for Human Perception (PhD)
Type（岗位类型）: Hardware
Citys（岗位城市）: Redmond, WA | Remote, US
Date（发布日期）: 2022-1-31
Summary（岗位介绍）
Reality Labs brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which together will become as universal and essential as smartphones and personal computers are today. And just as personal computers have done over the past 45 years, AR and VR will ultimately change everything about how we work, play, and connect. We are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interface, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. Some of those will advance much faster than others, but they all need to happen to enable AR and VR that are so compelling that they become an integral part of our lives.
We are looking for a skilled and motivated Visiting Researcher to join our team, whose mission is to build broad-coverage models of human perception and perceptually-driven outcomes. We are specifically looking for a candidate with experience in fields applicable to human-in-the-loop experimentation in human perception or related domains, and who can work with a team of researchers at the intersection between psychophysics, computational cognitive science, and machine learning. More broadly, this researcher 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 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Currently has, or is in the process of obtaining, a PhD degree in psychology, cognitive science, neuroscience, machine learning, statistics, data science, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
2+ years research experience in an area with potential applications to human-in-the-loop experimentation in human perception and related domains. Example areas include computational cognitive science, computational neuroscience, models and methods for psychophysics, active learning, deep Bayesian learning, Gaussian Process models, hierarchical/multitask models, or other relevant areas, as demonstrated via publications (conference or journal), open-source contributions, or similar venues.
1+ years of experience communicating and collaborating with other researchers, as demonstrated by collaborative projects or co-authored research presentations, material (publications/blog posts), or similar.
Must obtain work authorization in the 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 human-in-the-loop experimentation for perception and perceptually-informed outcomes.
Consult and collaborate with partner and client teams to deploy experimentation tooling in real experiments and experiences.
Additional Requirements（额外要求）
Experience with crossing disciplinary boundaries, for example from machine learning and statistics to cognitive science, from applied mathematics to neuroscience, or similar, as demonstrated by collaborations across disciplinary domains.
Experience creating research software used by others, for example as part of an academic collaboration, an open-source project, or equivalent.
Experience with SciPy/NumPy and at least one automatic differentiation framework (PyTorch, TensorFlow, JAX, Stan, etc.) -- PyTorch preferred.
Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
Experience working and communicating cross functionally in a team environment.
