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Postdoctoral Fellowship: Translational Disease Modeling

Bridgewater, New Jersey

Sanofi US' Bridgewater, NJ office location offers direct access to Somserset County's rich culture and diverse attractions. You can immerse yourself in art, explore history, and find fun entertainment and recreation all in one location. Sanofi US is proud to be a part of the Somerset County business community, which has so much to offer employees.

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Responsibilities

Discover your future…

Sanofi R&D works with passion to understand and solve some of the world’s most difficult biomedical problems facing patients and their healthcare providers. One of our assets in this quest are Post Doctoral Fellows, who bring an energy and desire to share our passion.

Sanofi’s Post Doctoral Fellowships offer a comprehensive training program that provides participants with the opportunity to advance their scientific careers in a leading-edge environment while contributing to Sanofi’s effort to bring next generation (transformative) solutions to patient’s most urgent medical needs.

Description:

The Translational Disease Modeling (TDM) Department is seeking to hire a highly motivated Postdoctoral Fellow to develop and apply quantitative systems pharmacology (QSP) models for the in silico evaluation of emerging novel targets in Immunology & Inflammation (I&I). The TDM group is part of the newly formed Digital & Data Sciences organization within R&D scientific operations platform. Sanofi provides a great multi-disciplinary environment to work and interact with extraordinarily talented and diverse group of people – all driven by innovative thinking and creativity. To this end, the Postdoctoral Fellow will be working on a highly stimulating and collaborative environment with biologists, clinicians, precision immunology scientists, pharmacometricians and in-house QSP as well as nonclinical modelers. This position is an exciting opportunity to impact critical decision making in drug R&D by coupling mechanism-based models of disease biology with drug pharmacology. The position will be based in Bridgewater, NJ.

Position Objectives:

  • Develop and apply QSP models to impact the progression of multi-target drug R&D in I&I.
  • Leverage relevant data (literature, in house) for model development, calibration and validation.
  • Contribute to translational (modeling & simulation) plans and assessments.
  • Promote QSP modeling both internally (within R&D) and externally (QSP scientific community).

Key Responsibilities:

  • Function as part of a team to design and develop multiscale computational models of disease pathophysiology and drug(s) mechanism of action.
  • Conduct extensive literature review to identify suitable mechanistic elements, interactions, rate constants and sub-modules for incorporation into models.
  • Develop and rigorously assess the functionality, feasibility, efficiency and validity of new models.
  • Analyze model predictions and identify suitable strategies to resolve issues (whenever occur) pertaining to model performance and inaccuracy.
  • Leverage algorithms for parameter optimization and parameter sensitivity analysis.
  • 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.

Basic Qualifications:

  • Recent PhD (0-3years) in biomedical/biochemical engineering, biophysics, applied mathematics, pharmacology or related field with a proven track record of productivity as demonstrated by publications and conference presentations.
  • Creative and innovative scientist who is passionate about developing a deep understanding of disease and disease mechanisms.
  • Solid 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.
  • Excellent oral and written communication skills and the ability to interact effectively with scientists in other disciplines with a positive, collegial and collaborative attitude.
  • Computational fluency and hands-on experience with one or more modeling and simulation packages or programming languages (MATLAB, R).
  • Strong commitment to on-the-job-training.
  • Must have US work authorization.

Preferred Qualifications:

  • Experience in building, validating and using QSP models or ODE-based models of biological pathways/systems.
  • Self-directed, independent, and highly-motivated researcher who excels in a collaborative, multi-disciplinary environment.
  • Primary authorship in peer-review scientific journals.
  • Familiarity with the challenges and general application of mathematical models in pharmaceutical R&D.
  • Strong attention to detail and analytical skills.
  • Demonstrated leadership skills.
  • Excellent communication and interpersonal skills.

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#LI-SA

Sanofi US Services, 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.

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.

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