Science and health

Genomics, multi-omics and biological data

Genomics, multi-omics and biological data work is about building models that read biological sequences and the molecular measurements that interact with them. AI companies need it to turn raw biology into predictions that scientists and clinicians can test and trust.

Labs and companies now generate sequence and molecular data faster than teams can interpret it, and model builders want to apply modern methods to it. The hires are tricky because the skills sit in different camps. Strong candidates understand the biology, the data pipelines and the modelling. Many only have two. Consent, population bias and batch effects also change what a result really means, so look for people who question their own data first.

Hiring now 2Emerging 2

Roles in this family

4 roles

Hiring nowGenomics Machine Learning ScientistA Genomics Machine Learning Scientist builds models of genomic variation and sequence function, and shows they hold up across populations and…Hiring nowAI Bioinformatics EngineerAn AI Bioinformatics Engineer builds the pipelines that turn raw biological data into clean, trustworthy inputs for models. Without that work, a…EmergingMulti-Omics AI ScientistA Multi-Omics AI Scientist builds models that combine several types of biological measurement, such as genomic, transcriptomic and proteomic data…EmergingBiological Foundation Model ResearcherA Biological Foundation Model Researcher builds broad models over biological sequences or molecular measurements, then shows they work on real…

Where the people come from

Bioinformatics, computational biology, genetics or ML

Not to be confused with. Genomic data require careful consent and population-valid interpretation.

Core skills

  • Probability and statistics
  • Data pipelines
  • Privacy engineering
  • Biomolecular modelling

Where it is used

  • Drug discovery and biotechnology
  • Genomics and bioinformatics

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