Overview
The LITIS laboratory at INSA Rouen Normandy is offering a postdoctoral position aimed at advancing machine learning applications in organic synthesis. This role is particularly significant as it merges computational techniques with chemical research, contributing to the optimization of organic reactions through innovative methodologies.
Background & Relevance
Machine learning has become an essential tool in various scientific fields, including chemistry. The integration of deep learning techniques, especially Graph Neural Networks (GNNs), into organic synthesis can enhance the modeling and optimization of chemical reactions. This approach not only accelerates research but also opens new avenues for discovery in synthetic chemistry, making it a vital area of study in the AI/ML community.
Key Details
- Position: Postdoctoral researcher in Machine Learning for Organic Synthesis
- Duration: 1 year
- Start Date: November 2025
- Location: INSA Rouen Normandy, France
- Collaboration: Institut CARMeN
- Salary: Approximately 3,500€ per month
- More Information: Application Details
- Contact Emails: benoit.gauzere@insa-rouen.fr, gilles.gasso@insa-rouen.fr
Eligibility & Participation
This postdoctoral position is targeted at researchers with a strong background in machine learning, particularly those who have experience in deep learning and its applications in chemistry. Candidates should be prepared to engage in collaborative research and contribute to ongoing projects within the LITIS lab.
Submission or Application Guidelines
Interested candidates should follow these steps to apply:
1. Review the detailed application information provided in the link.
2. Prepare your application materials, including a CV and cover letter.
3. Submit your application via the contact emails provided.
Additional Context / Real-World Relevance
The application of machine learning in organic synthesis is a growing field that promises to revolutionize how chemical reactions are approached. By leveraging advanced computational techniques, researchers can achieve greater efficiency and effectiveness in synthetic processes, which is crucial for both academic research and industrial applications. This position at INSA Rouen represents an opportunity to be at the forefront of this exciting intersection of AI and chemistry.
Conclusion
This postdoctoral position at INSA Rouen offers a unique chance to contribute to significant advancements in the field of organic synthesis through machine learning. Interested individuals are encouraged to explore this opportunity and apply, as it represents a valuable step in the integration of AI technologies within scientific research.
Category: PhD & Postdoc Positions
Tags: machine learning, deep learning, organic synthesis, INSA Rouen, chemistry-informed ml, GNNs, postdoc, research
