Facebook Research Intern, Magnetic Tracking in Redmond, Washington
Oculus Research's Surreal team is looking for the next generation of scientists and engineers to tackle the most ambitious problems in machine perception. One opening is now available for an intern throughout 2017 researching topics for new generations of augmented and virtual reality devices that have real-time space-aware computing at their core.
;Bayesian estimation for EM systems ;Finite Element modelling of EM systems ;Exotic EM sensor and computational devices ;Multimodality tracking and localization systems ;Full-stack AR systems for augmented and virtual reality
In particular we welcome PhD students wishing to work at the emerging intersection of magnetic sensing and estimation, as well as students with a strong background in EM simulation and modelling. We also welcome students with a passion for working in a strongly collaborative team that spans research across algorithms, hardware design and systems prototyping.
Our internships are twelve (12) to twenty four (24) weeks long and we have various start dates throughout the year.
Design, simulation, prototyping and analysis of experimental EM systems.
Design and implementation of estimation algorithms.
Collaboration with and support of other researchers across various disciplines.
Communication of research agenda, progress and results.
Pursuing a PhD in Electrical Engineering, or a related STEM field
Currently enrolled in a full time degree program and returning to the program after the completion of the internship.
2+ years experience with developing algorithms for Bayesian filtering, state estimation, numerical optimization, system identification.
2+ years experience with EM field simulation (using tools like Ansys Maxwell or similar).
1+ years experience with design and simulation of analog, digital and mixed-signal circuits.
Interpersonal skills: cross-group and cross-culture collaboration.
Ability to obtain work authorization in the United States in 2017.
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github).
Demonstrated EE engineer experience via an internship, work experience, academic or personal projects.
Proven track record of achieving results as demonstrated in accepted papers at top engineering conferences (e.g. IEEE conferences).
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