Job Description

ROLE SUMMARY

Quantitative Systems Pharmacology (QSP) is a discipline that uses mechanistic mathematical models and disease platforms to enhance the robustness and quality of decision-making from exploratory research through clinical development. We are seeking a highly motivated individual to develop and apply QSP models for the in silico evaluation of novel targets and compounds, including application to preclinical and clinical study designs and mechanistic interpretation of study results in support of development of breakthrough treatments in oncology, rare diseases, inflammation and immunology, or anti-invectives. The successful candidate will be responsible for integrating and sharing data and knowledge in a highly stimulating, collaborative, and multi-disciplinary environment to develop a deeper understanding of physiological systems and disease mechanisms within and across therapeutic areas.

ROLE RESPONSIBILITIES

Build and utilize QSP models of biological, physiological, and pathophysiological processes to evaluate novel targets, pathways, and drug candidates in oncology, rare cardiac disease, gene therapy, immunology, or other key therapeutic areas.

Work in close collaboration with biologists, clinicians, precision medicine scientists, clinical pharmacologists, pharmacometricians, QSP and nonclinical modelers, and other partner line colleagues to inform discovery and development programs and improve our understanding of disease mechanisms.

Serve as QSP modeling & simulation point-of-contact in multidisciplinary project teams to solve challenging problems in drug discovery and development; contribute to preclinical and clinical study design and mechanistic interpretation of data.

Develop and/or utilize state-of-the-art mathematical tools to gain insight into causal relationships between individual components of targets, pathways, and systems-level responses.

Analyze and interpret complex data sets in the context of disease mechanisms and pathways; develop a deep disease understanding and knowledge base.

BASIC QUALIFICATIONS

Ph.D. in Applied Mathematics, Engineering, Physics, Pharmaceutical Sciences, or related disciplines with strong background in mathematical, statistical, and numerical methods

0-5 years relevant experience (postdoc or equivalent in academia or industry) in developing differential equation-based models of biological and/or physiological systems

PREFERRED QUALIFICATIONS

Postdoctoral experience in QSP or biological systems modeling; prior experience in developing models with applications in oncology, cardiac disease, immunology, or gene therapy is desirable

Deep understanding of theory, principles, and statistical aspects of mathematical modeling and simulation, including numerical methods, parameter estimation/optimization, ordinary differential equations (ODEs), and how these can be applied in the development of complex models of biological pathways and systems

Computational fluency and hands-on experience with one or more modeling and simulation packages or programming languages (e.g., MATLAB, R, Julia, SimBiology, C/C++)

Creative and innovative early career scientist who is passionate about developing a deep understanding of disease and disease mechanisms with experience interacting with biology or clinical colleagues

Self-directed, independent, and highly-motivated researcher who excels in a collaborative, multi-disciplinary team environment

Excellent oral and written communication skills; ability to engage and effectively communicate within a cross-disciplinary team is highly valued

Primary authorship on relevant publications in peer-reviewed scientific journals