About this opportunity
Insilico Search Partners lists this Sr. Scientist, RNA Foundation Models opportunity in boston, Massachusetts. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Research Scientist, Machine Learning Foundation Models
About the Opportunity
A leading AI-driven drug discovery organization is seeking an exceptional Senior/Staff Machine Learning Scientist to help lead its core AI research team, with a specific focus on building Biological Foundation Models for RNA biology.
The Role
Lead the architecture, training, and scientific validation of large-scale foundation models on genomic, transcriptomic, and single-cell datasets, working in close partnership with computational biologists and drug developers to ensure models capture biologically meaningful, mechanistically grounded representations.
What You'll Own
Foundation Model Architecture: Deep emphasis on CNNs, Transformers, and sequence models (including state-space models) purpose-built for RNA and genomic sequence data.
Biological Grounding: Embed deep biological priors directly into model architectures and training objectives, tying model design to RNA biology and therapeutic mechanism.
Model Development at Scale: Implement, train, debug, and rigorously evaluate large-scale models, demonstrating scientific validity on frontier problems in RNA-based genetic medicine.
What You Bring
PhD (or equivalent demonstrated expertise) with a strong research focus in Computational Biology, Machine Learning, Computer Science, or a related quantitative field.
Deep, hands-on expertise building foundation models: CNNs, Transformers, and sequence/state-space models applied to biological or genomic sequence data.
Demonstrated track record building foundation models applied towards RNA
Strong PyTorch proficiency; experience training and debugging large-scale deep learning models
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Worksite address
boston, MA, 02298, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.