Associate Director Quantitative Systems Pharmacology (QSP) - Switch4 LLC
Cambridge, MA 02139
About the Job
Title: Associate Director Quantitative Systems Pharmacology (QSP)
Location: Cambridge, MA
Job-Type: FTE/Permanent
Seeking to hire a highly talented Quantitative Systems Pharmacology (QSP) modeling scientist to support its R&D portfolio. Modeling efforts represent key biological processes of the pathophysiology and a drug's mechanism of action to enhance the understanding of disease and therapeutic response. QSP-model based simulations allow prediction of drug efficacy in virtual patients. The successful candidate will be working within a dynamic, multidisciplinary environment to provide support for strategy and decision making in drug research and development. The position is based in Cambridge, MA.
Responsibilities:
• Design, build, and apply QSP modeling approaches to support decision making
• Interface with project team to identify opportunities, and to develop and implement innovative mechanistic modeling strategies
• Communicate modeling predictions to key stakeholders
• Collaborate with internal and external partners (CROs, consultants and academic collaborators) to support internal QSP efforts
• Identify and interpret preclinical and clinical data critical for model development and refinement
• Maintain state-of-the art knowledge of relevant modeling approaches and techniques
• Contribute to abstracts and manuscripts.
Requirements:
• Earned Ph.D. (in Biomedical Engineering, Applied mathematics, Systems Biology/Pharmacology or related field) and 5+ years of mathematical modeling & simulation experience within the pharmaceutical industry
• Track record of productivity, with evidence of independence in leading scientific projects
• Hands-on experience with programming languages like Matlab/R/Julia (Matlab preferred)
• Experience in differential equation- based models and parameter optimization approaches
• Understanding of theory, principles and statistical aspects of mathematical modeling and simulation
• Good understanding of cell biology and physiology, as well as the basic principles of pharmacokinetics and pharmacodynamics
• Strong project management skills including organization, time management and follow-up.
Location: Cambridge, MA
Job-Type: FTE/Permanent
Seeking to hire a highly talented Quantitative Systems Pharmacology (QSP) modeling scientist to support its R&D portfolio. Modeling efforts represent key biological processes of the pathophysiology and a drug's mechanism of action to enhance the understanding of disease and therapeutic response. QSP-model based simulations allow prediction of drug efficacy in virtual patients. The successful candidate will be working within a dynamic, multidisciplinary environment to provide support for strategy and decision making in drug research and development. The position is based in Cambridge, MA.
Responsibilities:
• Design, build, and apply QSP modeling approaches to support decision making
• Interface with project team to identify opportunities, and to develop and implement innovative mechanistic modeling strategies
• Communicate modeling predictions to key stakeholders
• Collaborate with internal and external partners (CROs, consultants and academic collaborators) to support internal QSP efforts
• Identify and interpret preclinical and clinical data critical for model development and refinement
• Maintain state-of-the art knowledge of relevant modeling approaches and techniques
• Contribute to abstracts and manuscripts.
Requirements:
• Earned Ph.D. (in Biomedical Engineering, Applied mathematics, Systems Biology/Pharmacology or related field) and 5+ years of mathematical modeling & simulation experience within the pharmaceutical industry
• Track record of productivity, with evidence of independence in leading scientific projects
• Hands-on experience with programming languages like Matlab/R/Julia (Matlab preferred)
• Experience in differential equation- based models and parameter optimization approaches
• Understanding of theory, principles and statistical aspects of mathematical modeling and simulation
• Good understanding of cell biology and physiology, as well as the basic principles of pharmacokinetics and pharmacodynamics
• Strong project management skills including organization, time management and follow-up.
Source : Switch4 LLC