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Postdoctoral Fellow in Imaging Photoplethysmography and Vital Sign Monitoring
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University of Arizona
Tucson, AZ (In Person)
$76,000 Salary, Full-Time
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Job Description
Postdoctoral Fellow in Imaging Photoplethysmography and Vital Sign Monitoring University of Arizona - 4.2 Tucson, AZ Job Details Full-time $68,000 - $84,000 a year 16 hours ago Benefits Health savings account Relocation assistance Health insurance Dental insurance Flexible spending account Tuition reimbursement Paid time off Vision insurance Professional development assistance Life insurance Retirement plan Qualifications AI models Digital signal processing Image processing Machine vision systems Scientific publications Design of experiments Electrical engineering Scientific research papers Research project design Doctor of Philosophy Computer vision research Working with students Ophthalmic diagnostic imaging equipment ECG monitoring Medical imaging Electrical Engineering Clinical data analysis Blood pressure monitors Machine learning frameworks Data analysis software Scientific reports Full Job Description Project summary The Arizona Center for Telemedicine and Digital Health at the University of Arizona seeks a postdoctoral fellow to develop and validate imaging photoplethysmography (iPPG/PPGI) methods for noncontact monitoring of vital signs, with emphasis on robust heart‑rate, heart‑rate variability, respiration , and cuffless blood‑pressure estimation . The role combines optical system design, video acquisition, signal processing, machine learning, and clinical validation to produce reproducible, bias‑aware algorithms and datasets suitable for translational research. Key responsibilities Design and implement video acquisition setups (RGB/IR cameras, illumination, synchronization with reference sensors). Develop signal‑processing pipelines for motion compensation, denoising, and pulse waveform extraction. Build and evaluate machine‑learning models for HR, HRV, respiration, and cuffless BP estimation with rigorous cross‑validation and bias analysis. Plan and run human subject studies including protocol design, ground‑truth collection (ECG, cuff BP), and IRB coordination. Perform statistical and clinical validation , including error analysis across skin tones, motion conditions, and demographics. Document and disseminate results via peer‑reviewed publications, open datasets, and code releases; contribute to grant writing. Mentor graduate and undergraduate students working on related tasks. Required qualifications PhD in Biomedical Engineering, Electrical Engineering, Computer Science, Applied Physics, or related field (completed within last 5 years or imminent). Strong background in signal processing and time‑series analysis (filtering, ICA, spectral analysis, pulse extraction). Demonstrated experience with computer vision / imaging (camera systems, exposure/frame‑rate control, OpenCV or equivalent). Proficiency in programming (Python; libraries such as NumPy, SciPy, PyTorch/TensorFlow, OpenCV). Experience designing or running human subject experiments and familiarity with physiological reference devices (ECG, clinical BP cuffs). Strong written and oral communication; record of publications or technical reports. Preferred qualifications Prior work on photoplethysmography, remote PPG, or cuffless blood‑pressure estimation . Experience with hardware prototyping (embedded systems, camera SDKs, synchronization). Knowledge of statistical validation and regulatory considerations for medical devices. Experience handling dataset bias and fairness evaluation (skin‑tone robustness). Familiarity with real‑time processing and optimization for low‑power platforms. Track record of open‑science practices (public datasets, reproducible code). Skills and competencies