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🚀 Internship

Research Scientist Intern, Motion Control Algorithm (PhD)

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Meta

16d ago

🚀 Off-cycle Internship

Sunnyvale

AI generated summary

  • The ideal candidate for the Research Scientist Intern position at Meta should have a Ph.D. in Mechanical Engineering or Electrical Engineering, with a strong focus on control. They should have deep knowledge of control theory, signal processing, and system identification algorithms, as well as expertise in using Matlab and Simulink. Experience with implementing control systems in embedded microcontrollers and proficiency in languages like MATLAB, C/C++, and Python is required. Strong interpersonal skills, the ability to communicate complex research effectively, and familiarity with motion control, sensor fusion, laser metrology, image analysis, and structural vibration fundamentals are preferred qualifications.
  • The Research Scientist Intern, Motion Control Algorithm at Meta will collaborate with researchers and cross-functional partners, while publishing impactful research results. They will focus on developing control algorithms, deploying them on hardware architectures, and prototyping and characterizing experimental systems and custom hardware.

Off-cycle Internship

Research & DevelopmentSunnyvale

Description

  • Meta 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.

Requirements

  • Currently has or is in the process of obtaining a Ph.D. degree in Mechanical Engineering, Electrical Engineering, or relevant technical field with a focus on Control
  • Deep knowledge of linear and nonlinear control theory, signal processing techniques, and system identification algorithms
  • Expertise in the use of Matlab and Simulink for modeling and simulation for electromechanical system
  • Expertise in systems characterization and identifications
  • Experience in implementing control systems in embedded microcontroller environments
  • Proficiency in languages such as MATLAB, C/C++, Python
  • Interpersonal skills: cross-group and cross-culture collaboration
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
  • Preferred Qualifications:
  • Intent to return to the degree program after the completion of the internship/co-op.
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at Journals or leading conferences
  • Ability to communicate complex research in a clear, concise and actionable manner
  • Familiarity with motion control of electromechanical systems
  • Familiarity with inertial navigation sensors and sensor fusion
  • Familiarity with laser metrology
  • Experience with image analysis and image processing
  • Knowledge of structural vibration fundamentals

Education requirements

Currently Studying
PhD

Area of Responsibilities

Research & Development

Responsibilities

  • Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
  • Publish research results that are both publishable and have direct impact on Meta products
  • Research on control algorithms development and deployment on hardware architectures
  • Prototyping, building and characterizing experimental systems and custom hardware

Details

Work type

Full time

Work mode

office

Location

Sunnyvale