Bioinformatics Machine Learning Researcher
Job Description
Develop and evaluate machine-learning approaches for biological data analysis.
What you will do
• Apply supervised and unsupervised methods to genomic, transcriptomic, proteomic and multi-omics datasets.
• Build and assess models for variant calling, expression analysis or biological pathways.
• Construct scalable, reproducible pipelines integrating biological analysis and ML.
• Document methods, assumptions and technical decisions.
Required background
• At least one first-author paper in a peer-reviewed journal.
• Demonstrated competence in both machine learning and bioinformatics.
• A relevant quantitative master’s or doctorate; suitable fields include bioinformatics, computational biology, computer science and data science.
• Independent technical problem-solving ability.
Preferred background
• Use of GATK, STAR, DESeq2, Nextflow, Snakemake or equivalent workflows.
• Teaching or teaching-assistant experience in ML, bioinformatics or computational biology.
• Familiarity with biological foundation models such as scVI, DNABERT or Enformer.
Availability
• Remote and asynchronous; plan for 10–20 hours weekly over two to three weeks, with scope and timing confirmed before starting.
Pay and engagement
Per project; fee agreed before work
The agreed project fee determines payment. Any hourly equivalent is an estimate, not an hourly-pay commitment.
Amounts are in USD. The applicable rate or fee and work requirements are agreed before you begin.