Principal Scientist, Translational Modeling & Decision Science
Tasks
- Apply regulatory credibility concepts for internal decisions
- Build mechanistic models for drug development decisions
- Compute probability of pharmacological success
- Curate ground truth and evaluate prediction quality
- Define context of use for decision engagements
- Deliver structured retrospectives on engagement outcomes
- Execute high consequence analyses with expert judgment
- Feed failure cases into regression tests and benchmarks
- Integrate evidence for due diligence and milestone decisions
- Prototype novel modeling approaches
- Quantify and communicate transparent uncertainty
- Quantify uncertainty in translational predictions
- Review autonomous outputs for scientific correctness
- Translate field discoveries into product requirements
Perks/Benefits
Skills/Tech-stack
Computational Biology | Drug development | Immunology | LLM | Language Models | Large Language Models | Machine Learning | Mechanistic modeling | Molecular Biology | NumPy | Numerical ODE | Pandas | Pharmacodynamics | Pharmacokinetics | Pharmacology | Physiology | Probability modeling | Python | Quantitative Analysis | SciPy | Systems pharmacology | Uncertainty Quantification
Education
Roles
Regions
Countries
States
Cities
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