Research Scientist, Neural Interfaces (PhD)

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.

Research Scientist, Neural Interfaces (PhD) Responsibilities:

• Build cutting-edge machine learning and signal processing models (event detection, sequence-to-sequence, signal separation, time series regression, etc.) to advance neuromotor interface capabilities.
• Plan and execute cutting-edge applied research to advance neural interface capabilities. Collaborate with engineering and HCI teams to translate fundamental scientific knowledge into new technology.
• Use quantitative research methods to define, iterate upon and advance key areas of our research agenda. Develop research-grade code for deployment in research prototypes.
• Collaborate with engineering and Human-Computer Interactions (HCI) teams to deploy models that leverage fundamental scientific knowledge into new technology and user experiences.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Currently in the process of obtaining a PhD in the field of deep learning, artificial intelligence, machine learning, computer science, robotics, computational neuroscience, signal processing, speech and language technologies, or related fields.
• Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. SciPy ecosystem) and machine learning (e.g. Scikit-learn, PyTorch, TensorFlow).
• Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly.
• 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.
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.

• Experience with cross-domain and cross collaboration.
• Experience in the analysis and modeling of high dimensional time series, such as neural signals, multi-channel 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 familiarity with real-time
• Experience in signal processing and familiarity with real-time signals.
• Experience with large scale cluster computing for machine learning modelling.
• First-authored publications at peer-reviewed conferences and journals.
• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).