Lead Research Scientist, Neural Interfaces

What you'll do

• Lead research efforts to develop state-of-the-art closed-loop algorithms for control for Brain Computer Interface (BCI) systems
• Design and drive execution on a multi-year research agenda
• Perform hands-on real-time and offline analysis of electrophysiological data obtained from non-invasive brain recordings
• Make an impact as a part of a multi-disciplinary research team building next-generation brain-computer interfaces for Augmented Reality
• Develop new experimental protocols for exploring capabilities enabled by brain-computer interfaces
• Share your expertise with team members and other stakeholders to drive BCI hardware and ML development

Knowledge, Skills & Abilities

• Comprehensive expertise in systems neuroscience with a focus on brain rhythms, neural features extraction and signal interpretation
• Strong knowledge of statistics and machine learning concepts
• Demonstrated ability to define, lead and execute challenging research projects
• Experience in analyzing complex data, driving insights, and communicating results in a simple and clear way to both technical and non-technical stakeholders
• Strong computer science fundamentals, problem solving skills, programming (Python)
• Proven ability to lead interns, PhD students, or junior researchers and engineers
• Proven ability to impact a product with cutting edge research technology

Minimum Qualifications

• PhD in computational neuroscience, systems neuroscience, machine learning, physics, computer science, electrical engineering, or related fields
• 7+ years of experience in performing Brain-Computer Interface research including experimental design, execution and interpretation
• Demonstrated ability to perform independent research
• Experience with applying advanced statistics and machine learning methods to physiological time series (MEG or EEG preferred)
• Experience in signal processing and familiarity with real-time signals
• Excellent communication skills and fluency in English

Preferred Qualifications

• Significant industry experience in a relevant role
• Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. Numpy/SciPy ecosystem) and machine learning (e.g. Scikit-learn, PyTorch, TensorFlow)
• Track record of publications in peer-reviewed research venues
• Conversation-level French is a plus