About the role
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
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