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Senior Biologist (maternity leave) at Cytoreason · Trevo
About CytoReason
CytoReason builds computational disease models that help pharmaceutical companies understand disease biology and make better R&D decisions. Our platform integrates large-scale public and proprietary omics data into models of immune-mediated and inflammatory diseases, used by leading pharma partners for target discovery, indication selection, and clinical development.
About the team
The Model Team builds, maintains, and interprets CytoReason's portfolio of disease models. Each team member owns a set of disease areas end to end - from data curation to biological interpretation to customer delivery. The team works at the interface of biology, data science, and engineering, and increasingly builds its own AI-based tools to scale scientific work.
What you'll do
We're looking for a disease biologist to take ownership of a portfolio of disease models, serve as the scientific point of contact for customers on those diseases, and help develop AI-driven workflows that make our science faster and more rigorous. This role suits someone who combines deep biological understanding with curiosity about computational and AI tools, and who learns new diseases and methods quickly.
Own a set of disease models end to end, including dataset selection, curation, model building, and biological QC
Interpret model outputs (differential expression, cell abundance, pathways, target associations) and assess whether results reflect real disease biology or artifacts
Present findings to pharma customers, translating complex analyses into clear scientific stories that support their R&D decisions
Quickly build expertise in new disease areas and indications as customer and portfolio needs evolve
Design and build AI-based tools and workflows (e.g. Claude skills and agents) for curation, QC, and reporting
Collaborate with product, R&D, and customer-facing teams to shape model improvements and new capabilities
Requirements
PhD in biology, immunology, computational biology, or a related field
Deep understanding of immunology and the biology of immune-mediated and inflammatory diseases
Hands-on experience analyzing transcriptomic data computationally - bulk RNA-seq, scRNA-seq, or both
Working proficiency in R and/or Python
Proven ability to learn new scientific domains fast and work independently
Excellent English, with strong presentation skills and confidence in front of scientific and industry audiences
Experience in:
Building with LLMs or AI tools in a scientific context (prompting, agents, automation)
Biotech or pharma, especially in customer-facing or translational roles
Multi-omics analysis (e.g. proteomics, metabolomics, scRNA-Seq or cross-omics integration)