Job Description
Job Title: Fall 2025 Post Doctoral Fellow - Process Modeling and CMC Data Science - Vaccines Location: Waltham, MA
About the Job The Postdoctoral Fellow position is located within the Data and Computational Science (DCS) department at the Sanofi mRNA Center of Excellence (mRNA CoE), supporting the CMC Data Science Group. This role focuses on developing multiscale mechanistic models to investigate the formation and production of lipid nanoparticles (LNPs) used in the delivery of nucleic acid therapeutics.
This is a unique opportunity to gain hands-on experience with mRNA technologies and unit operations, while demonstrating the impact of mechanistic, hybrid, and machine learning models in a non-GMP laboratory environment.
We are an innovative global healthcare company that helps the world stay ahead of infectious diseases by delivering more than 500 million vaccine doses a year. Across different countries, our talented teams are exploring new technologies to protect people and promote healthy communities. We chase the miracles of science every single day, pursuing progress to make a real impact on millions of patients around the world.
Main Responsibilities: - Develop multiscale mechanistic, hybrid, or machine learning models for LNP formation and production.
- Apply these models to characterize and optimize LNP manufacturing processes.
- Champion and implement model-based strategies to accelerate process development across Sanofi.
- Communicate progress through technical presentations and comprehensive reports to cross-functional stakeholders.
- Present and publish research findings at scientific conferences and in peer-reviewed journals.
About You Basic Qualifications: - PhD in Chemical Engineering, Biochemical Engineering, or Bioengineering.
- Experience with and understanding of mRNA unit operations, including in vitro transcription and LNP production.
- Experience with modeling and data analysis tools such as Python (Scikit-learn), Julia, MATLAB, PYOMO, and gPROMS.
- Proven track record of scientific publications and conference presentations.
Preferred Qualifications: - Publications related to LNPs, particularly those involving computational or modeling approaches.
- Experience with machine learning and hybrid modeling techniques.
- Familiarity with numerical algorithms for solving transport equations and population balance models.
- Excellent communication skills in a collaborative, international setting.
Why Choose Us: - 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.
- Exposure to cutting-edge technologies and research methodologies.
- Networking opportunities within Sanofi and the broader biotech community.
The salary for this position is $95,000 annual . All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs. Additional benefits information can be found through LINK .
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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All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs, and additional benefits information can be found here.
Job Tags
Permanent employment,