Senior Biomedical Signal Processing Scientist

LifeLens Technologies Inc.•Ivyland, PA

1d•Onsite

About The Position

LifeLens Technologies, Inc. is a medical device developer located in Ivyland, PA. We are pioneering innovative, next-generation treatment devices for personal health monitoring. We are seeking to hire a Senior Biomedical Signal Processing Scientist. In this role, you will have the opportunity to work on cutting-edge technologies designed to revolutionize wearable health care. You have a collaborative mindset and a passion for developing new technology. You are detail-oriented and goal-driven. You are a capable problem solver with excellent organizational skills and superior verbal and written communication skills. Your passion and drive will be rewarded with a competitive salary, benefits, and long-term growth opportunities. This is a full-time, on-site position. Summary You will develop and validate algorithms that turn signals from the Company's multi-sensor wearable hubs, including PPG, ECG, and accelerometry, into clinical and consumer health measurements. The role spans two kinds of work: offline analysis of high-volume clinical and field recordings, and real-time algorithms that run on the device. You will own algorithms from first prototype through clinical validation and regulatory submission, working closely with hardware, firmware, and clinical teams. As the Company expands into consumer products, you will help shape which measurements it offers and how they perform in everyday wear.

Requirements

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 expertise in MATLAB and willingness to transition to Python.
Experimental design and applied statistics, including method-comparison analysis.
Working knowledge of machine learning methods and when they are appropriate.
Data analysis and visualization skills.
Ability to own problems from open question to validated result.
Ability to communicate complex technical concepts effectively.

Nice To Haves

Experience with PPG, ECG, SpO2, respiration, or other biosignal algorithms.
Background in neural or cardiac electrophysiology or optical recording (e.g., calcium imaging, fiber photometry, cardiac optical mapping).
Experience with event detection and point-process analysis in noisy time series.
Experience with motion-artifact reduction and sensor fusion.
Experience with real-time or embedded algorithms; working knowledge of C.
Experience developing medical devices under FDA design controls, such as 510(k) submissions.

Responsibilities

Designing and validating algorithms that derive physiological measurements from multiple sensors, including PPG, ECG, and accelerometry.
Conducting offline analyses of large clinical and field datasets to discover, characterize, and quantify signal behavior, failure modes, and algorithm performance.
Developing methods robust to motion artifact and other real-world conditions.
Adapting validated algorithms for real-time use on the device, working with firmware engineers on implementation.
Designing and analyzing validation studies against clinical reference devices, using statistically sound methods of agreement and accuracy.
Producing verification and validation evidence and documentation to support regulatory submissions.
Writing efficient, tested, and reproducible code.
Communicating results to technical and nontechnical audiences.
Collaborating across engineering disciplines to solve problems, improve existing products, and meet deadlines.
Mentoring junior team members.
Other tasks as assigned.