Research Scientist, Neural Interfaces - Machine Learning

Reality Labs is seeking an AI 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 leverage state-of-the-art ML to push the limits of non-invasive neuromotor interfaces.

Research Scientist, Neural Interfaces - Machine Learning Responsibilities:

• Research and develop machine learning models that leverage biosignals to advance neural interface capabilities
• Build cutting-edge machine learning and signal processing models (event detection, sequence-to-sequence, signal separation, time series regression, data compression, data augmentation etc.)
• Use quantitative research methods to define, iterate upon and advance key areas of our research agenda

• Obtained a PhD in the field of computational neuroscience, machine learning, computer science, electrical engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. SciPy ecosystem) and machine learning (e.g. Scikit-learn, PyTorch, JAX, TensorFlow)
• Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly
• 3+ years of experience working autonomously to design, execute, interpret, and present research studies
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

• Experience working and communicating cross-functionally in a team environment
• Experience in signal processing and familiarity with real-time signals
• Experience with large scale cluster computing for machine learning modelling
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, COSYNE or similar