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

Work arrangement
Yes