Research Scientist, Machine Learning for Audio (PhD)

Company: Facebook
Location: Redmond, Washington, United States
Type: Full-time
Posted: 08.JUN.2021


Facebook Reality Labs Research (FRL-R) brings together a world-class team of researchers, developers, and engineers to create the future of ...


Facebook Reality Labs Research (FRL-R) brings together a world-class team of researchers, developers, and engineers to create the future of augmented and virtual 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 interfaces, 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. The audio team within FRL-R is looking for a Research Scientist with a broad set of skills in computational modeling applied to audio/acoustics. The role involves the application of computational modeling techniques, including machine learning, deep learning and statistical learning methods, to problems in spatial audio, room acoustics, auditory perception, audio-visual navigation, acoustic scene understanding, and other topics related to augmented and virtual reality.

  • Develop novel computational models to solve complex research problems in the areas of spatial audio, room acoustics, and machine and/or human auditory perception
  • Design and implement state-of-the-art audio/acoustics computational models and machine learning techniques on PyTorch, TensorFlow, or other platforms
  • Help build experimental design pipelines and generate reliable, correct spatial audio, room acoustics and machine and/or human auditory perception datasets for model training/validation/testing
  • Identify and debug common issues in training machine learning models such as overfitting/underfitting and leakage
  • Collaborate with and support other research scientists and engineers within the Audio Team and the larger FRL Research organization
  • Collaborate with external academic groups to advance our research goals

  • Currently has, or is in the process of obtaining, a PhD in the field of Audio, Acoustics, Machine Learning, Computer Science, Computer Engineering, Electrical Engineering, Perception or a related field
  • 3+ years experience with development and implementation of audio processing methods
  • 3+ years experience with development and implementation of machine learning or deep learning algorithms applied to audio and/or acoustics
  • 3+ years experience with scientific programming languages such as Python, C++, or similar
  • Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

  • Experience with audio signal processing applied to spatial audio and/or room acoustics
  • Experience with auditory perception
  • Experience with building computational models on speech and/or acoustic datasets
  • Proven track record of achieving significant results and innovation as demonstrated by first-authored publications
  • Interpersonal skills to facilitate cross-group and cross-culture collaboration

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.

Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at . - provided by Dice

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