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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Quantitative Systems Pharmacology (QSP) modeling and simulation, with a strong foundation in mathematical and statistical methods applied to drug discovery and development. Proficient in analyzing complex biological datasets and integrating multi-modal data to derive insights for project teams.
Highest-signal resume keywords
PhD In Applied MathematicsQSP Modeling And SimulationMathematical ModelingComputational Experience With MATLABExperience With Large Language Models
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Quantitative Systems PharmacologyMathematical ModelingStatistical MethodsNumerical MethodsOrdinary Differential EquationsMechanistic ModelingData AnalysisScientific Machine LearningParameter EstimationOptimization
Soft Skills
CollaborationCommunicationProblem-Solving
Tools & Technologies
MATLABSimBiologyJuliaPythonC/C++
Industry Keywords
Pharma Life ScienceBiomedical IndustryBiological PathwaysImmunologyMetabolic DiseasesInflammatory DiseasesFibrotic DiseasesOmics DataMulti-Modal DataClinical Pharmacology
Tech Stack
Tools & technologiesPythonC++
About the role
Key responsibilities & impact- Build and utilize QSP models of biological, physiological, and pathophysiological processes
- Evaluate diseases, pathways, disease progression, drug candidates, and treatment modalities
- Collaborate with biologists, clinicians, clinical pharmacologists, QSP and nonclinical modelers, and partner-line colleagues
- Serve as a disease-area QSP lead with expertise in disease pathophysiology, biomarkers, clinical endpoints, experimental methodologies, and data
- Serve as the QSP modeling and simulation point of contact on project teams
- Contribute to preclinical study design and mechanistic data interpretation
- Develop and/or utilize mathematical tools to analyze causal relationships in drug-target-biomarker-disease-patient interactions
- Analyze and interpret complex datasets in the context of disease mechanisms and pathways
- Explore synergies between QSP and computational approaches involving human genetics, functional genomics, and AI/ML
- Assess the scientific rigor and biological suitability of QSP models through context-driven verification and validation
Requirements
What you’ll need- PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with experience in the application of mathematical and statistical methods
- 2 or more years of experience in Pharma Life Science Biomedical industry developing and applying QSP approaches to drug discovery or development programs
- Experience with the theory, principles, and statistical aspects of mathematical modeling and simulation
- Knowledge of numerical methods, parameter estimation/optimization, and ordinary differential equations (ODEs)
- Experience applying mathematical modeling and simulation to complex models of biological pathways and systems
- Computational experience with one or more modeling and simulation packages or programming languages, such as MATLAB, SimBiology, Julia, Python, or C/C++
- Solid biological understanding of immunology and previous experience applying mechanistic modeling to metabolic, inflammatory, or fibrotic diseases
- Experience translating modeling and simulation analyses into knowledge and insights for project teams
- Experience with Large Language Models (LLMs) and Agentic AI
- Experience applying scientific machine learning (SciML) approaches to mechanistic modeling
- Experience integrating omics and/or other multi-modal data with mechanistic models
Benefits
Comp & perks- Annual bonus
- Eligibility to participate in the share based long term incentive program
- Health care and other insurance benefits for employee and family
- Retirement benefits
- Paid holidays
- Vacation
- Paid caregiver/parental and medical leave
- Comprehensive benefits program for US employees