PhysioNet Competitor (Biomedical Signal Processing & ML)

Remotebridge; United States; On-site; USD 83,000 - 165,000; Part time

Benefits offered by this job

Remote work

Flexible hours

Job summary

Remotebridge is seeking contractors with experience in physiological signals and biomedical data to tackle advanced problems in AI systems. You will apply scientific programming, signal processing, and modeling to create, solve, and evaluate tasks; start immediately; ~15 hours per week; fully remote globally.

Strong candidates will explain methods, experiments, and decisions; prior AI training project experience is not required.

Qualifications

• Experience directly with physiological signals and noisy real-world data.
• Ability to explain methods, experiments, and decisions clearly.
• Familiarity with scientific programming and modeling.

Responsibilities

• Create technically rigorous, self-contained problems involving biomedical signals and machine learning.
• Develop reference solutions using Python, MATLAB, or similar tools.
• Tackle tasks on signal preprocessing, feature extraction, or forecasting.

Skills

Biomedical signal processing

Machine learning

Python

MATLAB

Time-series analysis

Tools

Python

MATLAB

Job description

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

Our team is engaging specialists with experience in the PhysioNet Challenge or comparable biomedical signal processing and machine learning competitions. In this role, you will apply your scientific programming, signal processing, and modeling expertise to create, solve, and evaluate advanced technical problems that help improve next-generation AI systems.

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.

Compensation Structure

Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.

Minimum submission requirements apply.

Start Timeline & Availability

• We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.