Computational Biologist - Quantitative Methods & Target Discovery
US: Boston MA Lilly Seaport Innovation Center, United States
USD 166K-266K Senior-level Full Time
Tasks
- Advance Bayesian and causal modeling approaches
- Advise teams through code review and collaborative analysis
- Analyze functional genomics workstreams
- Build convergent evidence frameworks for target prioritization
- Build scalable preprocessing qc harmonization pipelines
- Collaborate with statistics and AI teams to co develop models
- Design end to end multimodal omics analyses
- Develop knowledge graphs for target discovery
- Develop multimodal representation learning and foundation models
- Develop predictive models for target scoring
- Differentiate association from mechanism using causal reasoning
- Influence reproducible scalable analytical workflows
Perks/Benefits
- N/A
Skills/Tech-stack
Artificial Intelligence | Bayesian Methods | CRISPR screens | Causal Graphs | Causal Inference | Foundation Models | Generative Models | Graph Neural Networks | Knowledge graphs | Machine Learning | Metabolomics | Multi-Omics | Multi-Omics Integration | Neural Networks | Omics integration | Perturb-seq | Proteomics | Python | R | Representation Learning | Reproducible Research | Single-cell | Single-cell Transcriptomics | Spatial proteomics | Spatial transcriptomics | Version control | Workflow Orchestration
Education
Roles
Biologist | Computational Biologist | Data Scientist | Scientist
Regions
Countries
States
Cities
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