Proteomics Machine Learning Expert

This is a remote, project-based role for machine learning professionals with deep expertise in proteomics. You will complete tasks at the intersection of ML and proteomics — including model development, data analysis, and research tasks applied to real protein and mass spectrometry datasets. Work is over the next 2–3 weeks, asynchronous, and assigned on a project-by-project basis, with an expected commitment of 10–20 hours per week for the projects you accept.

Published researcher with at least one first-author publication in a peer-reviewed journal. Demonstrated expertise in both machine learning and proteomics (e.g., mass spectrometry data, protein databases, or related biological datasets). Master's or PhD in Computational Biology, Bioinformatics, Computer Science, Data Science, or a related quantitative field. Responsibilities: Apply machine learning techniques to proteomics data, including protein identification, quantification, and structure-function prediction tasks. Build, train, and evaluate ML models tailored to mass spectrometry and proteomic datasets. Develop predictive models using supervised and unsupervised learning approaches relevant to biological data. Optimize model performance through feature engineering, hyperparameter tuning, and domain-specific preprocessing. Document methodologies, model assumptions, and technical approaches clearly and reproducibly. Benefits: Exceptional Pay ($150–$200/hour). Portfolio Building. Professional Growth. Startup Exposure (Y Combinator-backed). Flexible Time Commitment.