PhysioNet Competitor Biomedical Signal Processing ML

You will create self-contained problems based on real physiological signals and develop clear reference solutions. Your work will provide technical training data for AI systems.

You will use Python, MATLAB, or a similar scientific computing tool to solve tasks involving biomedical signals, time-series data, signal processing, and machine learning.

• Create challenging problems based on real physiological signals.
• Develop reference solutions in Python, MATLAB, or a similar scientific computing environment.
• Design tasks involving preprocessing, filtering, segmentation, feature extraction, representation learning, classification, or forecasting.
• Validate your methods and make sure the work can be reproduced.
• Submit work that meets the project specifications.

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Time:
  Approximately 15 hours per week, with part-time contract work.
• Experience level:
  Entry level listing, with specialized technical requirements.
• Language:
  Fluent English.
• Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
• Have participated in a Physio Net/CinC Challenge or a comparable biomedical signal processing or scientific machine learning competition.
• Show a strong personal technical contribution with public evidence, such as a team result, paper, repository, technical report, or meaningful code contribution.
• Have hands-on experience with ECG, EEG, PPG, EMG, respiratory signals, polysomnography, or other clinical time-series data.
• Proficient in Python, MATLAB, or another scientific computing language.
• Prior AI training experience is not required.

AI training work uses examples prepared and reviewed by people to help artificial intelligence systems learn. Specialized contributors are paid for technical knowledge because their work helps make complex training data accurate and useful.