Research Scientist, Neuromotor Interfaces (EMG Signal Validation)
Meta

Meta is seeking a Research Scientist with deep expertise in product-focused signal processing and sensor development to help us create novel wearable devices and algorithms that will become one of the main pillars for interaction with the virtual and augmented world. Help us unleash human potential by removing the bottlenecks between user intent and action.Our team uses machine learning and statistical signal processing tools to advance our pioneering work building a practical, non-invasive, wearable human-computer interface that draws on rich neuromotor signals. We are a multi-disciplinary group of researchers and engineers who work closely with partner hardware, firmware, ML algorithms, and user experience teams to model and understand real-world use cases, set requirements for hardware performance, and develop software strategies to improve signal quality and product performance.

Research Scientist, Neuromotor Interfaces (EMG Signal Validation) Responsibilities:

• Define sensor performance requirements, and characterize the dependencies between sensors and overall system performance, in collaboration with hardware, and algorithms teams
• Design and analyze experiments (numerical simulations, bench tests, and human-in-loop studies) to characterize sensor performance under real-world conditions
• Explore and design new sensing architectures and characterize their impact on downstream ML models and product experience

Minimum Qualifications:

• Ph.D. in computer science, electrical engineering, mechanical engineering, statistics, applied mathematics, signal processing, control theory, machine learning, bioengineering or related technical fields
• Record of peer-reviewed publication demonstrating research excellence
• Research-oriented software engineering skills (e.g. SciPy ecosystem)
• 5+ years of experience working autonomously to design, execute, interpret, and present research studies
• 2+ years of experience as technical lead for a project or initiative of 2+ individuals
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

Preferred Qualifications:

• Experience with human-in-loop sensor development. e.g. biosensors or human-computer input devices such as electrocardiography (ECG), photoplethysmography (PPG), electromyography (EMG), capacitive touch sensing
• Experience with design of experiments and test methods for evaluating sensor hardware performance (e.g. aggressor studies and simulations, hardware phantoms)
• Experience in statistical signal processing, control systems, and machine learning
• Experience partnering with hardware engineering teams
• Experience defining research/technical direction for a team and supporting the work of a small group of researchers toward those goals

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