PhysioNet Competitor (Biomedical Signal Processing & ML)

PhysioNet Competitor (Biomedical Signal Processing & ML)

  
Pay: $60–$120/hour

Location: Global, fully remote

Job Type: Contractor (~15 hours per week)

Schedule: Flexible-you choose the hours and days you work, including weekends if desired

We are looking for people who have worked directly with physiological signals and can turn noisy, real-world data into a rigorous and reproducible analysis. Strong candidates will be able to explain the methods they developed, the experiments they ran, the technical decisions they personally owned, and how they validated their results. No prior experience working on AI training projects is required.

Scope of Work
Create technically rigorous, self-contained problems involving biomedical signals, time-series data, signal processing, and machine learning.
Develop clear reference solutions using Python, MATLAB, or another appropriate scientific computing environment.
Work with tasks involving signal preprocessing, filtering, segmentation, feature extraction, representation learning, classification, or forecasting.

Preferred Qualifications
Participation in a PhysioNet/Computing in Cardiology Challenge or a comparable biomedical signal processing or scientific machine learning competition.
Strong competition results and evidence of a substantive personal technical contribution.
Public evidence of your work through an official team result, conference paper, technical report, open-source repository, or meaningful code contribution.
Hands-on experience with physiological signals such as ECG, EEG, PPG, EMG, respiratory signals, polysomnography, or other clinical time-series data.

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