<p>Meta is seeking a Research Scientist to help us unleash human potential by eliminating the bottlenecks between intent and action. To achieve this, we're building a practical neural interface drawing on the rich motor neuron signals that can be measured non-invasively with neuron-level resolution. Our research lies at the intersection of computational neuroscience, machine learning, signal processing, statistics, biophysics, motor learning, perceptual psychophysics, and human-computer interaction. We're looking for people who want to shape the future of this technology and are excited about joining our collaborative research team</p> <p>Qualifications: Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience PhD in the field of machine learning, artificial intelligence, computer science, electrical engineering, robotics, signal processing, or related fields 1+ year of industry experience in the field of artificial intelligence, machine learning, computer science, robotics, signal processing, or related fields Expertise/familiarity with hardware sensors such as Inertial Measurement Units Research-oriented software engineering skills, including fluency with libraries for scientific computing and machine learning (for example Scikit-learn, PyTorch, TensorFlow) Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly Experience in the analysis and modeling of high dimensional time series, such as neural signals, multichannel audio recordings, robotic sensory signals, financial time series, video, or other sensor modalities Experience developing end-to-end ML pipelines, including: dataset preprocessing, model development and evaluation, and software integration Experience in signal processing and control theory and familiarity First-authored publications at peer-reviewed conferences and journals Experience with large scale cluster computing for machine learning modeling</p> <p>Responsibilities: Research and develop machine learning models that leverage Inertial Measurement Unit sensors Build cutting-edge machine learning and signal processing models (event detection, sequence-to-sequence, signal separation, time series regression, etc.) Use quantitative research methods to define, iterate upon and advance key areas of our research agenda</p>