Post Doctoral Fellow – Computational Modeling: Sanofi is seeking a highly motivated Postdoctoral Research Fellow to contribute to the advancement of autonomous experimentation through cutting-edge machine learning (ML) algorithms. This position, based in Cambridge, MA, focuses on revolutionizing drug development by harnessing the power of artificial intelligence (AI) in process design and synthetic molecule manufacturing. The post-doctoral fellow will play a crucial role in developing a reaction network generator and applying active learning methodologies to optimize knowledge extraction and kinetic model development from experiments.
Post Doctoral Fellow – Computational Modeling and Machine Learning
Designation: Postdoctoral Research Fellow
Research Area: Computational Modeling and Machine Learning in the context of autonomous experimentation for drug development.
Location: Cambridge, MA
Eligibility/Qualification:
- Ph.D. (must hold or receive by the start date) in chemical engineering, chemistry, computational/theoretical chemistry, or a related field.
- Proficient understanding of synthetic reaction transformations and in-depth expertise in mechanistic analysis.
- Expertise in Deep Learning architectures, including Graph Neural Networks (GNNs), active learning, and reinforcement learning.
- Strong background in computational chemistry, demonstrated by applying computational techniques to address complex chemical challenges.
- Proficient in Python programming.
- Excellent written and oral communication skills.
- Ability to collaborate with interdisciplinary teams.
Job Description: The Postdoctoral Fellow will:
- Build an AI/ML model for generating reaction networks based on existing chemical knowledge.
- Integrate quantum chemistry tools, external databases, and literature data to provide comprehensive lists of possible reactions.
- Develop and apply filters/rules based on thermodynamics and reaction feasibility.
- Implement and optimize active learning algorithms to guide experiment selection for efficient data acquisition and model improvement.
- Collaborate with data scientists and experimentalists to integrate the developed tool into an automated AI-assisted kinetic learning algorithm.
How to Apply: Interested candidates should:
- Submit a motivated application
- Provide a detailed Curriculum Vitae
- Include Certificates/Diplomas (MSc and PhD)
- List publications with examples of the most relevant ones attached as separate pdf-files
- Include reference letters and other relevant qualifications.
The application deadline is posted as “Posted 6 Days Ago,” suggesting an urgent application submission.
Last Date for Apply: Until position filled
