Work Location: Bucks County, Pennsylvania

Summary:

Seeking a scientist to develop and validate algorithms that transform multi-sensor wearable data into clinical and consumer health measurements. The role involves both offline analysis of large datasets and real-time algorithm development, with opportunities to contribute to clinical validation and product development.

Responsibilities:

• Design and implement algorithms to extract physiological measurements from sensor data such as PPG, ECG, and accelerometry.
• Analyze large-scale clinical and field recordings to assess signal quality, identify failure modes, and evaluate algorithm performance.
• Develop robust methods to address motion artifacts and other real-world signal challenges.
• Create and maintain data processing pipelines and analytical tools for signal analysis.
• Adapt algorithms for real-time deployment on wearable devices and support integration efforts.
• Participate in the design and analysis of validation studies comparing outputs to clinical reference standards.
• Contribute to documentation for verification, validation, and regulatory submissions.
• Write efficient, reproducible code and communicate technical results to diverse audiences.

Qualifications:

• PhD, Master's, or Bachelor's degree with 2+ years of relevant experience in biomedical engineering, electrical engineering, neuroscience, physics, applied mathematics, computer science, or a related quantitative field.
• Research experience, including graduate research, is considered relevant experience; recent graduates are encouraged to apply.
• Strong foundation in digital signal processing and time-series analysis.
• Experience analyzing physiological or real-world sensor signals through research, coursework, or industry.
• Proficiency in Python; MATLAB experience is a plus.
• Skills in experimental design, applied statistics, data analysis, and visualization.
• Familiarity with machine learning methods and ability to learn new domains quickly.
• Clear communication of technical results to both technical and nontechnical audiences.
• Preferred: Experience with PPG, ECG, SpO2, remote PPG, respiration, or other biosignals; background in neural or cardiac electrophysiology or optical recording; event detection in noisy time series; version control, testing, and reproducible workflows; familiarity with C or embedded systems; exposure to medical device development or regulated environments.

Published Category: Analytical & Process Development