Position Description

Our team is looking for a Co-Op student with an interest in solving challenging AI/ML problems using biomedical signal processing and wearable technology. Through this opportunity, you will work with a multi-disciplinary team

consisting of engineers, scientists, and clinicians to prepare and process large biomedical and physiological datasets (e.g.,PPG, accelerometry, EOG, EEG, commercial-off-the-shelf wearable data, etc), develop and evaluate machine learning algorithms, and implement data visualization tools for advanced prediction and inference of physiological status (i.e. fatigue, illness, stress, etc). We are looking for students who are self-motivated

and interested in signal processing, machine learning, deep learning, statistical pattern recognition, and high-performance computing.

Requirements/Skills

• The candidate is a student in a B.S., M.S., or Ph.D. program in Biomedical Engineering, Electrical Engineering, Computer Science, or other relevant degree.
• Experience with Python, MATLAB and machine learning (coursework or practical)

Preferred (not required)

• Biomedical signal processing and/or time series analysis experience
• Experience with Python and deep learning libraries like: Pytorch, JAX, and/or keras
• Interest in AI meta-learning, foundation models / self-supervised learning, continual learning, one-shot and/or transfer learning

Compensation for 2026

• Technical Co-Op: $24.50 – $31.00 per hour (based on year in school)
• Administrative Co-Op: $21.50 – $25.00 per hour (based on year in school)