Research Scientist Intern, Sensor System Benchmarking (PhD)

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Research Scientist Intern, Sensor System Benchmarking (PhD)
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Redmond, WA
Facebook Reality Lab Research is looking for upcoming scientists and researchers with great interest in sensor system benchmarking for various use cases for future AR/VR devices and algorithm/hardware/software co-optimization. Our internships are twelve (12) to twenty-four (24) weeks long and we have various starting dates throughout the year.
Research Scientist Intern, Sensor System Benchmarking (PhD) Responsibilities
  • Analyze image data captured by our uniquely developed image sensor.
  • Perform system benchmarking by collecting various corner-case dataset using existing dataset collection rig.
  • Execute SLAM benchmarking pipeline and analyze system KPI.
  • Correlate between image quality and KPI result, find the approach to optimize performance with sensor, exposure setting, and ISP.
  • Participate in various sensor, image, and system related research activities.
Minimum Qualifications
  • Currently has, or is in the process of obtaining a PhD in Electrical Engineering, Computer Science or related field.
  • Experience with image sensor systems (camera, ISP, algorithm).
  • Programming, simulation and modeling experience with language such as C/C++, Python, Matlab.
  • Experience with image analysis and image processing with language such as Python, Matlab.
  • Demonstrated sensor system benchmarking experience from small sensor system to complex design 2+ years of lab experience carrying out independent research.
  • Interpersonal skills: 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.
Preferred Qualifications
  • Intent to return to degree-program after the completion of the internship/co-op.
  • Experience in sensor modeling and algorithm simulation/design.
  • Track record of publications with focus in image processing, computer vision, application optimization.
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