Principal Scientist Quantitative Systems

Sanofi•Cambridge, MA

About The Position

We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Are you ready to shape the future of medicine? The race is on to speed up drug discovery and development to find answers for patients and their families. Your skills could be critical in helping teams accelerate progress. Join our Quantitative Systems Pharmacology (QSP) group as a Principal Scientist and you'll support our R&D portfolio with mechanistic disease modeling. Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions. About Sanofi: We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Requirements

PhD in systems pharmacology/biology, computational biology, biomedical engineering, or a related field with a strong record of productivity demonstrated through publications and scientific presentations with at least 2 years of Postdoctoral experience in disease modeling/QSP
Master’s degree with 4+ years of relevant industry experience, OR
Proficiency in mathematical modeling using differential equations.
Extensive experience in computational tools such as MATLAB, Julia and R (MATLAB preferred).
Excellent oral and written communication skills.
Ability to quickly learn pathophysiology in indications of interest, and treatment approaches in immunology.
Highly motivated, detail-oriented, and independent researcher.
Able to thrive in a collaborative, multi-disciplinary team environment.
Strong commitment to on-the-job-training.

Nice To Haves

Experience in drug discovery/development a plus, especially in bioinformatics or pharmacometrics.
Knowledge of Immunology

Responsibilities

Function as part of a team to develop and apply multiscale computational models of complex diseases based on detailed biological mechanistic knowledge to support model-informed drug discovery & development.
Survey literature to gain understanding of critical physiological processes to be represented, and identify suitable mechanistic elements, data, parameters and assumptions to be included.
Identify and analyze suitable internal preclinical and clinical data to inform modeling activities.
Analyze simulation results and identify appropriate strategies to resolve issues pertaining to model performance and accuracy.
Maintain extensive documentation of model development process, and data analysis.
Maintain quantitative systems pharmacology expertise through comprehensive education undefined
Communicate modeling predictions to key stakeholders.

Benefits

Bring the miracles of science to life alongside a supportive, future-focused team.
Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks’ gender-neutral parental leave.
Be part of a pioneering biopharma company that engages patients early in drug development and uses their insights to design studies that reflect real-world needs.
Help improve the lives of millions of people globally by making drug development quicker and more effective.
Work at the forefront of drug discovery, harnessing cutting-edge AI, data, and digital platforms to push the boundaries of science.

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