Bioinformatics Machine Learning Expert

This is a remote, project-based role for machine learning professionals with deep expertise in bioinformatics. You will complete tasks at the intersection of ML and biological data analysis - including model development, pipeline construction, and research tasks applied to real genomic, transcriptomic, or multi-omics 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. This position offers exceptional pay, exposure to cutting-edge biotech problems, and a strong addition to your research portfolio. **Responsibilities** * Apply machine learning techniques to biological datasets, including genomic, transcriptomic, proteomic, or multi-omics data * Build, train, and evaluate ML models tailored to bioinformatics applications such as variant calling, gene expression analysis, or pathway modeling * Develop predictive models using supervised and unsupervised learning approaches relevant to biological systems * Design and optimize bioinformatics pipelines integrating ML components for scalable, reproducible analysis * Document methodologies, model assumptions, and technical approaches clearly and reproducibly **Required Qualifications** * Published researcher with at least one first-author publication in a peer-reviewed journal * Demonstrated expertise in both machine learning and bioinformatics (e.g., sequence analysis, genomics, transcriptomics, or related biological data domains) * Strong problem-solving skills and ability to work independently on technical tasks * Master's or PhD in Bioinformatics, Computational Biology, Computer Science, Data Science, or a related quantitative field **Preferred Qualifications** * Experience with standard bioinformatics tools and workflows (e.g., GATK, STAR, DESeq2, Nextflow, Snakemake, or similar) * Background in TA'ing or teaching bioinformatics, ML, or computational biology courses * Familiarity with biological foundation models or large-scale omics ML frameworks (e.g., scVI, DNABERT, Enformer) Why apply * Exceptional Pay – Project-based pay ranges from $150–$200/hour * Startup Exposure – Work directly with an early-stage Y Combinator-backed company, gaining hands-on experience that sets you apart * Flexible Time Commitment – Work on your schedule while tackling meaningful scientific challenges * Portfolio Building – Gain experience applying ML to frontier bioinformatics problems * Professional Growth – Sharpen your skills on complex, real-world biological datasets and models