Principal Scientist - Process Modelling
Framingham, Massachusetts Permanent Posté le Apr. 01, 2025 Expire le Apr. 08, 2025Job title: Principal Scientist - Process Modelling
Location:Framingham, MA
About the Job
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 our teams accelerate progress.
The Principal Scientist, Process Modelling will be based in the Global CMC Development group in Research & Development (R&D) and will provide process modelling and advanced analytics support for biological process development.
With a formal training as a process systems engineerand a specialization in process modelling, you will have demonstrated skills in the field of mechanistic and hybrid modelling methodologies to support process design, optimization, and process control activities for biopharmaceuticals. You will also have familiarity with machine learning/data-driven modelling methodologies to support these applications.
The main focus for this position will be on the development and deployment of process models for downstream unit operations such as chromatography columns, viral inactivation and filtration units (UF/DF and viral filtration). However, prior experience with modelling methodologies to support upstream unit operations (e.g. bioreactor modeling, media development/optimization) will be considered a plus.
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. Ready to get started?
Main Responsibilities:
As part of matrix project teams, develop and deploy mechanistic, hybrid and data-driven modelling solutions to support downstream and upstream process development activities fora broad range of biopharmaceuticals.
Use programming languages such as Python, MATLAB, R to translate complex mathematical models into clean and reusable codes for model use and implementation.
In coordination with the process development group and working closely with the Data Science team, design and analyzetargeted experiments required to calibrate and verify model performance.
Act as a change agent to support the implementation of process modelling in established process development workflows for targeted downstream and upstream unit operations.
Track progress against deliverables and maintain a communication plan with key stakeholders and partners across departments.
Document your modelling work with rigorous scientific communication via technical presentations, reports and, when appropriate, scientific publications.
About You
For this position, domain knowledge in biologics downstream process development and manufacturingis required. Familiarity with upstream unit operations is a plus.
This is an exciting opportunity to demonstrate the benefits of process modelling and data science in a cutting-edge scientific department developing the next generation of Sanofi medicines that will improve the quality of life for patients across the world.
Basic Qualifications:
Process systems engineer/modelerwith a PhD in Chemical/Biochemical Engineering and a minimum of 3 years of industrial experience, or MSc with 6years ofindustrial experience.
Proven track recordof developing process models for downstream unit operations for biologics, e.g., affinity/ion exchange chromatography, ultra/ nano / tangential flow filtration etc. for process design, scale-up, scale-down and/or process control purposes.
Demonstrated ability to translate mathematical models into computer programs using programming languages such as MATLAB, R, Python or similar.
Domain knowledge in Biology with industrial or academic experience in downstream process developmentand/or manufacturing.
Excellent communication skills in an international environment.
Preferred Qualifications:
Demonstrated knowledge and application of Machine Learning / Multivariate analysis methodologies to biological processes. Proven knowledge of transfer learning methodologies is a plus.
Proven track record of developing process models for upstream unit operations (e.g. bioreactors), and familiarity with applications such as media development/optimization and model-based design of experiments.
Knowledge/ experience with process simulation software (e.g.gPROMS, DSPX) and integrated systems modelling applications (i.e. flowsheet modelling).
Solid track record of publications in the field of process modelling/process simulation in peer reviewed journals.
Beyond technical skills you will also have a solid track record in project management with an ability to communicate with transparency with your peers and with senior stakeholders.
This cross functional role will require intellectual agility to work across site/function boundaries in Sanofi’s global CMC organization.
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.
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.
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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