Chemical Computational Scientist – Machine Learning & Molecular Modeling for mRNA Vaccine Delivery
Chemical Computational Scientist – Machine Learning & Molecular Modeling for mRNA Vaccine Delivery
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* Department: Data & Computational Sciences, mRNA Center of Excellence
* Reports To: Director, Data & Computational Sciences (DCS)
Position Overview
The Data & Computational Sciences (DCS) department is at the forefront of transforming mRNA vaccine development through data science, predictive modeling, and molecular simulations. We are seeking a passionate and innovative Computational Scientist to join our cross-functional team and lead the development of machine learning (ML)-driven approaches for the design and optimization of lipid nanoparticle (LNP) components that improve mRNA delivery efficacy, thermostability, and biodegradability.
This role is critical to supporting the global mRNA R&D strategy—advancing our understanding of LNP mechanisms, standardizing research methodologies, and ensuring long-term competitiveness in vaccine delivery innovation.
Key Responsibilities
* Lead the design and execution of coarse-grained molecular dynamics (CG-MD) simulations to extract molecular descriptors (e.g., membrane thickness, lipid order, charge distribution, LNP organization) that inform ML models.
* Integrate structural and physicochemical descriptors (e.g., molecular fingerprints, partition coefficients, TPSA, MW) with ML pipelines to generate predictive insights.
* Develop and optimize machine learning models for screening and prioritization of novel ionizable lipids (ILs) and other LNP components based on predicted biological and physicochemical properties.
* Conduct computational docking studies to explore IL–protein interactions and generate bioactivity-relevant features for ML integration.
* Collaborate with chemists, biologists, and data scientists to interpret results, validate hypotheses, and guide synthesis and preclinical studies.
* Maintain and enhance reproducible computational workflows and contribute to the development of a standardized modeling platform for global research use.
* Present scientific findings to internal stakeholders and contribute to high-impact publications, patents, and strategy documents that shape Sanofi’s mRNA vaccine pipeline.
Required Qualifications
* Ph.D. in Computational Chemistry, Biophysics, Computational Biology, Molecular Modeling, or a related field; equivalent industrial experience will be considered.
* Proven expertise in molecular dynamics (MD) simulations, especially coarse-grained modeling approaches (e.g., MARTINI).
* Strong track record in machine learning applied to chemical and biological systems, including data preprocessing, feature engineering, and model validation.
* Proficiency with molecular descriptor generation tools (e.g., RDKit, PaDEL), and docking platforms (e.g., AutoDock, Schrödinger).
* Proficient in Python and familiar with libraries such as scikit-learn, PyTorch/TensorFlow, NumPy, and scripting in HPC environments.
* Strong understanding of lipid-based drug delivery systems, membrane biophysics, and molecular interactions.
* Excellent collaboration and communication skills, with the ability to translate computational results into actionable experimental insights.
Preferred Qualifications
* Prior experience in mRNA therapeutics or vaccine delivery systems.
* Background in AI-guided molecular design, virtual screening, or de novo generation of compounds.
* Familiarity with cloud-based computational environments and workflow management systems (e.g., Snakemake, Nextflow).
* Publications or patents in the fields of computational drug delivery, ML in chemistry/biology, or mRNA-LNP systems.
Seniority level
* Seniority level
Mid-Senior level
Employment type
* Employment type
Full-time
Job function
* Job function
Research
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Medical insurance
Vision insurance
401(k)
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