Machine Learning Bioinformatics Expert

What You'll Do5

• Train and test machine learning models on genomic, transcriptomic, proteomic, and multi-omics data sets.
• Apply supervised and unsupervised learning to biological questions, including variant calling, gene expression analysis, and pathway modeling.
• Create predictive models that capture patterns in biological systems and measure their performance.
• Assemble bioinformatics pipelines with ML steps that support scalable, reproducible analysis.
• Write down model assumptions, methods, and technical choices so another researcher can reproduce the work.

Requirements7

• First-author publication in a peer-reviewed journal.
• Hands-on background in machine learning and bioinformatics, with work spanning sequence analysis, genomics, transcriptomics, or another biological data domain.
• Master's or PhD in bioinformatics, computational biology, computer science, data science, or another quantitative field.
• Record of solving technical problems without close supervision.
• Familiarity with common bioinformatics tools and workflows such as GATK, STAR, DESeq2, Nextflow, or Snakemake.
• Experience with biological foundation models or large-scale omics ML frameworks such as scVI, DNABERT, or Enformer.
• Teaching or TA experience in bioinformatics, machine learning, or computational biology.

Who Should Apply

Published researchers with a first-author paper, graduate training in a quantitative field, and project work across ML and omics data fit this role. The strongest match brings comfort with independent technical problem solving and can point to specific models, pipelines, or biological datasets they have handled.

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