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About the position
At Sanofi, we chase the miracles of science, and we know mRNA has a role to play in the future of health. And while the pandemic has shaken up our industry, creating new opportunities and risks, we believe the acceleration of innovation with mRNA technology means vaccines and treatments for more people faster than before. That's why we're looking for bold, optimistic world-changers to join our mRNA Center of Excellence. We're investing €400m a year into the new Center, hiring a team of 450 dedicated employees, and focusing on implementing an integrated end-to-end mRNA vaccine capabilities and research with R&D, digital and CMC teams. Bring your ambition and optimism and join us on our journey to discover and deliver transformative medicine to patients through the advancement of our cutting-edge mRNA technology! As an RNA Machine Learning Co-op, you will participate in a 6-month project in the areas of cheminformatics, bioinformatics, computational biology, and machine learning to the task of developing and implementing first-in-class and best-in-class computational solutions and models for screening, optimizing and evaluating RNA molecules for mRNA-based vaccines and therapeutics as part of the Data and Computational Science team in the mRNA CoE. This team brings end-to-end data integration and advanced analytics (pre-clinical, biomarkers, process development, CMC, clinical) in the mRNA CoE. Deploying and exploiting digital solutions (AI/machine learning, data, analytics) to integrate the full data value chain, extracting actionable information for a move to a full data driven strategy and decision-making process, to increase probability of success and to accelerate mRNA vaccines and therapeutics development and launch.
Responsibilities
- Collaborate with group experts in the development and execution of the scientific strategy and technical solutions to develop best-in-class mRNA vaccines and therapeutics
- Execute development of a project to deliver data and computational solutions for the integration of chemical, structural, and biological data to support data analytics and visualization
- Design, develop, and validate robust analytical and machine learning approaches to support in silico characterization, screening, optimization, and analysis of mRNA molecules
- Collaborate internally to develop scientific hypotheses and drive new scientific insights based on computational frameworks
- Develop, deploy, and assess the results of at-scale models at varying levels of model granularity encompassing heterogeneous preclinical and clinical data
- Employ machine learning methods such as deep learning, neural networks, reinforcement learning, graphical, and generative models to deconvolve high dimensional experimental and in silico modeling results
- Maintain a well-documented, reusable codebase, and traceable model history
- Maintain awareness of latest developments in relevant fields, evaluate and apply as warranted
- Demonstrate good software engineering practices
- Proactively identify, assess, and internalize emerging technologies and methods
Requirements
- Currently pursuing a PhD or master's degree in Cheminformatics, Bioinformatics, Computational Chemistry, Computational Biology, Computer science, or related quantitative disciplines at an accredited college or university with the expectation that you will complete your current degree by the Spring of 2027
- Must be enrolled in school the semester following your internship/co-op with Sanofi
- Must be able to relocate to the office location and work 40hrs/week, Monday-Friday, for the full duration of the co-op/internship
- Must have permanent US work authorization
- Experience in computational and statistical analysis, quantitative modeling, and machine learning algorithms
Nice-to-haves
- Fluency in scientific computing (e.g., python, R)
- Practical experience proposing, prototyping, and deploying novel algorithms; developing and validating new models
- Demonstrated record of transforming algorithms/theory into practical applications delivering robust models that are high performance, interpretable and actionable
- Experience with software development good practices (code versioning, testing, etc.)
- A creative problem solver, skilled in divergent thinking and turning complex data into actionable insights and knowledge
- Good communication, scientific writing, and presentation skills; ability to simplify complex problems and communicate complex solutions in a simple and effective manner
- Understanding of vaccine development processes is a plus, as well as familiarity with RNA processes and RNA-centric techniques/methods
- Fluent in English
Benefits
- High-quality healthcare
- Prevention and wellness programs
- At least 14 weeks' gender-neutral parental leave
