Scientist – QSP (Systems Pharmacology)

Job description

Job Description:

The Translational Disease Modeling (TDM) group of Sanofi is seeking to hire a highly talented scientist to support its portfolio. The TDM group is part of the Digital Data Sciences (DDS) organization and supports critical decision making for Sanofi’s pipeline across drug development stages. The individual will primarily be involved with hands-on quantitative systems pharmacology (QSP) modeling activities focusing on Oncology and Immuno-Oncology (I/O), to ensure delivery of projects aligned with the strategic needs of the company. The position will be based in Bridgewater, NJ or Cambridge, MA.

Position Objectives:

·  Develop computational systems models via internal and external collaborative efforts to enhance the understanding of disease mechanisms and to guide therapeutic intervention strategies.
·  Leverage relevant preclinical and clinical data to augment modeling and simulation capabilities.
·  Communicate, with clarity, modeling predictions, in presentations, to key stakeholders.
·  Contribute to translational plans and assessments.

Key Responsibilities:

·  Function as part of a team to design and develop multiscale computational models of complex biological systems based on detailed biological mechanistic knowledge.
·  Collaborate with internal and external members to survey literature and gain understanding of critical biological pathways and physiological processes.
·  Develop and rigorously assess the functionality, feasibility, efficiency and validity of new models.
·  Analyze model predictions and identify suitable strategies to resolve issues pertaining to model performance and inaccuracy.
·  Develop and implement algorithms for parameter optimization and parameter sensitivity analysis.
·  Conduct extensive literature review to identify suitable mechanistic elements, interactions, rate constants and sub-modules for incorporation into models.
·  Communicate technical material to internal and external audiences
·  Maintain quantitative systems pharmacology expertise through comprehensive education including attendance and participation in conferences, scientific workshops etc.

Qualifications:

·  PhD with an excellent track record of productivity in the areas of systems pharmacology/biology, computational biology or related field, as manifested by publications and scientific presentations in prestigious conferences.
·  Excellent communication skills to effectively communicate research findings in a highly-matrixed organization.
·  Proficiency in mathematical modeling and programming as demonstrated by hands-on experience in a variety of computational tools such as MATLAB, Julia and R.
·  Strong commitment to on-the-job-training.

Knowledge And Skills Desirable But Not Essential:

·  Expert knowledge in immunology or cancer biology.
·  Basic experience in Pharmacometrics or Clinical Pharmacology.
·  Experience with high performance and cloud computing model implementation.

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

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At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.