Job title: Upstream Process Development & Technologies
Main responsibilities:- Drive the modelling strategy across multiple concurrent projects and programs, setting direction for mechanistic, statistical, hybrid, and machine learning approaches in cell culture development.
- Lead AI solution development and implementation for cell culture processes, identifying high-impact opportunities and translating them into deployed, production-ready tools.
- Mentor junior scientists and engineers in modelling methodologies, AI tools, and data science workflows, fostering a strong modelling culture within the team.
- Own the end-to-end model lifecycle - from problem framing, data curation, and model design through validation, deployment, monitoring, and continuous improvement.
- Present technical findings, modelling results, and strategic recommendations to senior leadership and cross-functional stakeholders.
- Contribute to regulatory filings, technical documentation, and CMC packages, ensuring modelling approaches meet scientific rigor and regulatory expectations.
- Establish and champion modelling standards, best practices, and governance frameworks to ensure reproducibility, traceability, and scientific rigor across all modelling activities.
- Influence departmental strategy for digitalization and modelling integration, serving as a key voice in shaping the future of upstream process development capabilities.
- Lead and design complex CHO upstream process development studies at lab scale, defining experimental strategy and aligning approaches to broader program goals.
- Represent Sanofi externally at industry conferences, in publications, and through collaborative partnerships, building Sanofi's scientific reputation in bioprocess modelling and AI.
- Manage timelines and deliverables across multiple concurrent projects, ensuring alignment with program milestones and organizational priorities.
- Prepare experimental protocols, perform troubleshooting, and author high-quality technical reports and scientific documentation.
About you- Master's degree with 2+ years of experience OR PhD with 0+ years of experience in Biotechnology, Biology, Biochemistry, Chemical Engineering, Computational Biology, or a related discipline (academic experience will be considered)
- Demonstrated modelling focus in one or more of mechanistic cell models, machine learning, AI, or multivariate analysis, with tangible project outputs and deployed solutions.
- Demonstrated expertise in computational modelling applied to bioprocess or biological systems, with a track record of implementing models that directly influenced process decisions at program or platform level.
- Strong background in AI tool development and implementation, including model packaging, deployment, and integration into scientific workflows.
- Deep experience with mechanistic modelling (e.g., kinetic models, Monod-type growth models, metabolic flux analysis) and/or machine learning methods (regression, classification, neural networks, Gaussian process regression).
- Strong command of statistical methods and experimental design: DoE, PCA/PLS, multivariate data analysis.
Preferred:
- Hands-on experience in CHO or mammalian cell culture process development, with the ability to execute experiments and interpret results independently.
- Experience with transfer learning and Bayesian optimization approaches across datasets.
Technical Skills:
- Advanced to expert level experience with mechanistic (kinetic, metabolic), ML (random forest, neural networks, GPR), and hybrid modelling approaches.
- Proficiency in AI/ML frameworks and familiarity with generative AI tools and LLM applications in scientific workflows.
- Cloud Computing: Experience with cloud platforms and MLOps tooling for model deployment, versioning, and management
- Track record of implementing models that influenced process decisions at program or platform level.
- Statistical Methods: DoE, PCA, PLS, regression, multivariate analysis.
- Bioprocess Tools: MVDA software (SIMCA, JMP), LIMS, bioreactor data systems.
- Cell Culture: CHO bioreactor operation (HTP, benchtop, pilot scale), standard analytical methods.
Soft Skills:
- Modelling thought leadership: ability to define and advocate for a modelling vision across scientific and business stakeholders.
- Strategic thinking and ability to influence modelling adoption across functions and organizational levels.
- Stakeholder management and presentation skills, including experience communicating to senior leadership.
- Project management capabilities with demonstrated ability to balance and prioritize multiple concurrent modelling and experimental projects.
- Collaborative mindset with experience working at the interface of experimental and computational teams.
- Strong scientific curiosity and drive to push the boundaries of AI and modelling in bioprocess science.
- Ability to work with aggressive timelines and adapt to rapid changes in project priorities.
The salary range for this position is:
$100.500,00 - $145.166,66
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 the LINK.
