Postdoctoral Research Scientist - Array Signal Processing/ML (PhD)
- Woodinville, WA
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 Reality Labs Research 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 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. In particular, the FRL Research audio team is focused on connecting people by allowing them to feel together despite being physically apart, and allow them to converse in even the most difficult listening environments. We are looking for someone with strong interest and experience applying signal processing and ML/DL techniques to characterize the interaction of multiple complex acoustic systems. Such methods may include filter design, array processing, adaptive methods, and application of neural networks for system identification as well as for the equalization or calibration of linear systems. The role requires a background on audio signal processing, and machine- and deep-learning preferably applied to audio signals. Additional competences on acoustic engineering and spatial sound technologies are a plus.
- Develop novel algorithms and signal processing techniques to solve complex acoustic research problems in the field of spatial sound field reproduction.
- Implement state of the art methods for personalized calibration and equalization of electro-acoustic systems that can adapt to various acoustic conditions to demonstrate proof-of-concept and proof-of-experience.
- Leverage machine learning and deep learning techniques in Augmented and/or Virtual reality applications.
- Collaborate with team members across a variety of domains including signal processing, machine learning, acoustic engineering and perception sciences.
- Currently has, or is in the process of obtaining, a PhD and/or postdoctoral assignment in the field of Audio Engineering and Signal Processing, Acoustics, Electrical Engineering, Computer Science, or a related field.
- 3+ years of experience in array or multi-channel signal processing.
- 3+ years of experience in machine- and deep learning applied to audio problems.
- 3+ years of programming experience in MATLAB, Python or C/C++, and deep learning frameworks such as Pytorch, Tensorflow, or Keras.
- Interpersonal experience: 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.
- Research experience in one or more of the following: Audio, Augmented Reality, Virtual Reality.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at relevant journals or conferences, e.g. IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), NeurIPS, ICML, IEEE MLSP, Acoustical Society of America (ASA), and Audio Engineering Society (AES).
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