Senior Biomedical Signal Processing Scientist - WearableTech

LifeLens Technologies Inc.; Ivyland (PA); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Health Insurance

Dental & Vision Insurance

Paid Time Off

401(k)

Stock option incentive plan

FSA & dependent care

Job summary

LifeLens Technologies, Inc. in Ivyland, PA, is seeking a Senior Biomedical Signal Processing Scientist to develop algorithms for wearable health monitoring. You will own methods from prototype through clinical validation, collaborating with hardware, firmware, and clinical teams.

You will design DSP-based solutions for PPG, ECG, and accelerometry, validate them on large datasets, and adapt them for real-time device use, with a focus on robustness to motion and real-world conditions.

Qualifications

• PhD with relevant experience in biomedical signal processing.
• Experience with physiological signals (PPG, ECG) and sensor fusion.
• Strong experimental design and applied statistics skills.
• Familiarity with FDA design controls is a plus.

Responsibilities

• Design and validate algorithms converting multi-sensor signals into clinical and consumer measurements.
• Conduct offline analyses of large clinical/field datasets to characterize signal behavior and algorithm performance.
• Develop real-time algorithms for device deployment with firmware teams.
• Plan and execute validation studies against clinical references with rigorous statistics.
• Produce verifiable documentation to support regulatory submissions.
• Mentor junior team members and collaborate across disciplines.

Skills

DSP

Time-series

Physiological signals

Statistics

Machine learning basics

Data visualization

Mentoring

Communication

Education

PhD in Biomedical Eng. / Electrical Eng. / Neuroscience / Physics / Applied Math

MS in related field (5+ years)

BS in related field (7+ years)

Tools

Python

MATLAB

Job description

LifeLens Technologies, Inc. in Ivyland, PA, is seeking a Senior Biomedical Signal Processing Scientist to develop algorithms for wearable health monitoring. You will own methods from prototype through clinical validation, collaborating with hardware, firmware, and clinical teams.

You will design DSP-based solutions for PPG, ECG, and accelerometry, validate them on large datasets, and adapt them for real-time device use, with a focus on robustness to motion and real-world conditions.