Broad Institute of MIT and Harvard
Computational Biologist II
- Lead computational development for PROSPECT, analyzing 100K+ small-molecule compounds through screening QC, dose-response modeling, clustering, hit prioritization, and mechanism-of-action inference.
- Built a 10B+ compound virtual-screening pipeline for MoA inference and candidate prioritization, guided selection-algorithm design, and evaluated strategies for scaffold generalization and biological relevance.
- Developed a deterministic medicinal-chemistry triage system integrating structural liabilities, drug-likeness metrics, applicability-aware ADMET predictions, and TB chemical precedent into a reproducible human-review workflow for final compound selection.
- Develop quantitative target and mechanism methods, including gene-set curation and weighted, null-comparison, and threshold-free ranking to benchmark biological signal against known antibiotic mechanisms. Integrate CRISPRi phenotypes and compound-perturbation data to support mechanism-of-action interpretation.
- Partner with experimental scientists to define analytical requirements and go/no-go criteria for screening and assay development; optimized API-driven microbial-genomics workflows across 15M+ sequences and 11+ taxa to reduce diagnostic turnaround by more than two days.