Post-Doctoral Researcher in Machine Learning/Deep Learning for Organic Synthesis

INSA Rouen Normandy is the leading public engineering school in Normandy, known for its high-quality education, cutting-edge research, and commitment to scientific outreach. Founded in 1985, the school combines engineering excellence with strong humanist values. With over 2,000 students and 450 staff members, INSA Rouen offers a dynamic and innovative working environment. Located in a green area near Rouen, the school fosters both personal and professional development.

The research team « Apprentissage » of the LITIS laboratory is recruiting at INSA Rouen Normandy for a postdoctoral position in machine learning/deep learning for reaction optimization in organic synthesis. 

The postdoctoral fellow will conduct high-impact research in machine learning and deep learning applied to the organic synthesis. It is expected development of theoretical, algorithmic contributions in machine learning for chemistry, in particular the modeling of organic reactions based on large amounts of experimental data.

The intended research will target applications to fundamental problems in organic chemistry such as regioselectivity, optimization of the chemical yield of a reaction, minimization of by-products and finally prediction of diastereoisomeric ratios and/or enantiomeric ratios. 

First, classical machine learning models will be analyzed to identify the most relevant predictive features and to build robust models of reaction outcomes. The research will then move toward geometric deep learning, leveraging graph neural networks (GNNs) to represent reacting molecules as structured objects. GNNs naturally encode both the topology of molecular graphs and the chemical properties of atoms and bonds, providing a powerful framework for predicting reaction behavior and optimizing synthetic pathways. A major scientific challenge will lie in the integration of quantum-level information into these graph-based representations. Such information is not only difficult to incorporate, but also crucial, as quantum effects fundamentally govern reaction outcomes. By targeting advanced geometric deep learning enriched with quantum information, this research is expected to advance both the theoretical foundations of molecular modeling and the practical applications of data-driven organic synthesis.
The successful candidate will work at the LITIS Laboratory in collaboration with Institut CARMeN (UMR 6064), an internationally renowned laboratory specializing in methodology development in organic synthesis. 
 

• A PhD degree in machine learning, data science, or a related field
• A strong publication record in machine/deep learning
• Experience (or strong interest) in chemistry-informed machine learning will be appreciated
• Solid programming skills (Python, machine learning/deep learning frameworks)
• A good command of Scientific English
• The ability to work in a multidisciplinary environment
   

• Contract type: Fixed-term (CDD)
• Start date: November 1, 2025
• Duration: 12 months
• Working hours: Full-time (35h/week), daytime schedule
• Gross monthly salary: 3,500€
• Location: INSA Rouen Normandie, Madrillet Campus, with occasional travel

Joining INSA Rouen Normandie means working in a stimulating and supportive environment at the heart of academic excellence. We offer: A modern workplace promoting work-life balance, flexible working hours with additional leave days, access to sports and cultural activities, on-site catering services and free parking, a strong commitment to diversity and gender equality. 

Applications including:
 

• Cover letter
• Detailed CV
• Summary of past research and main publications
• Full texts of key publications
• Contact details of two referees

are to be sent to  benoit.gauzere@insa-rouen.fr, gilles.gasso@insa-rouen.fr and drh-recrutement@insa-rouen.fr  with the following « Postdoctoral Researcher in Machine and Deep Learning for Chemistry »

Interviews will be held in mid to late October 2025