Senior Biomedical Signal Processing Scientist

ClinLab Solutions Group; Ivyland (PA); On-site; USD 120,000 - 170,000; Full time

Job summary

ClinLab Solutions Group seeks a Senior Biomedical Signal Processing Scientist to develop and validate algorithms for wearable health monitoring devices. This role covers offline data analysis and real-time algorithm development from prototyping to clinical validation and regulatory support.

Collaboration across engineering disciplines and opportunities for mentorship are available. The position requires a PhD with 2+ years, or a Master's with 5+ years (or Bachelor's with 7+ years), strong

Qualifications

• PhD with 2+ years, master's with 5+ years, or bachelor's with 7+ years of relevant experience.
• Degree in biomedical engineering, electrical engineering, neuroscience, physics, applied mathematics, computer science, or a related quantitative field preferred.
• Strong foundation in digital signal processing and time-series analysis.
• Experience developing algorithms for physiological or other noisy real-world sensor signals.
• Expertise in Python, or MATLAB with willingness to transition to Python.
• Experience with FDA design controls and medical device regulatory submissions is preferred.

Responsibilities

• Develop and validate algorithms to extract physiological measurements from multi-sensor data, including PPG, ECG, and accelerometry.
• Analyze large-scale clinical and field recordings to assess signal behavior, identify failure modes, and evaluate algorithm performance.
• Create robust methods to address motion artifacts and other real-world signal challenges.
• Adapt and implement validated algorithms for real-time use on embedded devices in collaboration with firmware engineers.
• Design and analyze validation studies using clinical reference devices and statistically sound methods to ensure accuracy and agreement.
• Generate verification and validation documentation to support regulatory submissions.
• Write efficient, reproducible, and well-tested code for algorithm development and deployment.
• Communicate technical results clearly to both technical and non-technical audiences, and collaborate with multidisciplinary teams to solve problems and mentor junior staff.

Skills

Python

MATLAB

DSP

Time-series analysis

Machine learning

Data visualization

Education

PhD

Master's

Bachelor's

Tools

C

Job description

Senior Biomedical Signal Processing Scientist

Summary:

Seeking a Senior Biomedical Signal Processing Scientist to develop and validate algorithms for wearable health monitoring devices. This role involves both offline analysis of large datasets and real-time algorithm development, with responsibilities spanning from initial prototyping to clinical validation and regulatory support. The position requires strong collaboration across engineering disciplines and offers opportunities for mentorship and technical leadership.

Responsibilities:

• Develop and validate algorithms to extract physiological measurements from multi-sensor data, including PPG, ECG, and accelerometry.
• Analyze large-scale clinical and field recordings to assess signal behavior, identify failure modes, and evaluate algorithm performance.
• Create robust methods to address motion artifacts and other real-world signal challenges.
• Adapt and implement validated algorithms for real-time use on embedded devices in collaboration with firmware engineers.
• Design and analyze validation studies using clinical reference devices and statistically sound methods to ensure accuracy and agreement.
• Generate verification and validation documentation to support regulatory submissions.
• Write efficient, reproducible, and well-tested code for algorithm development and deployment.
• Communicate technical results clearly to both technical and non-technical audiences, and collaborate with multidisciplinary teams to solve problems and mentor junior staff.

Qualifications:

• PhD with 2+ years, master's degree with 5+ years, or bachelor's degree with 7+ years of relevant experience (postdoctoral and research experience counts).
• Degree in biomedical engineering, electrical engineering, neuroscience, physics, applied mathematics, computer science, or a related quantitative field preferred.
• Strong foundation in digital signal processing and time-series analysis.
• Experience developing algorithms for physiological or other noisy real-world sensor signals.
• Expertise in Python, or MATLAB with willingness to transition to Python.
• Skills in experimental design, applied statistics, and method-comparison analysis.
• Working knowledge of machine learning methods and their appropriate application.
• Proficiency in data analysis and visualization.
• Ability to independently manage projects from concept to validated result.
• Excellent communication skills for conveying complex technical concepts.
• Experience with PPG, ECG, SpO2, respiration, or other biosignal algorithms preferred.
• Background in neural or cardiac electrophysiology or optical recording (e.g., calcium imaging, fiber photometry, cardiac optical mapping) is a plus.
• Experience with event detection, point-process analysis, motion-artifact reduction, and sensor fusion is desirable.
• Familiarity with real-time or embedded algorithms and working knowledge of C is advantageous.
• Experience developing medical devices under FDA design controls, such as 510(k) submissions, is preferred.