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The Department of Molecular Chemistry in Grenoble is a joint research unit (UMR 5250) affiliated with the CNRS and the Université Grenoble Alpes, conducting research in various fields of molecular chemistry. The DCM comprises approximately 150 people whose scientific focus is geared towards major societal themes: health and well-being, and new energies, as well as fundamental aspects.
The unit is structured into six thematic teams, each with a team leader responsible for its organization, coordination, and administrative, scientific, and technical aspects. The successful candidate will join the SITh (Spectrometry, Interactions, and Theoretical Chemistry) team, where they will conduct research in theoretical chemistry.
https://dcm.univ-grenoble-alpes.fr/

Under the leadership of Anne Milet, the SITh team comprises three UGA lecturer-researchers, two CNRS researchers, a CNRS CPJ and a CNRS BAP E research engineer (scientific computing). The team also hosts a doctoral student and three post-doctoral researchers.

The mission involves developing a methodology integrating AI, delta-learning, MD, and QM/MM to describe deep eutectic solvents, build a foundational model for their structural and dynamic properties, and then analyze reaction mechanisms in solution. The objective is to link microscopic structures, interactions, solvent effects, and reactivity.

• Development of a foundation model for DES (GNN, FF+, delta-learning, etc.)
• Creation, processing, and validation of datasets from MD, QM, and QM/MM
• Training and optimization of neural networks
• Analysis of solvation structures and associated properties
• Study and rationalization of reaction mechanisms in DES
• Analysis, interpretation, and dissemination of results (publications, conferences, etc.)
• Regular interaction with project partners

The work environment is predominantly academic and based in the Department of Molecular Chemistry (DCM). There are no particular physical constraints associated with the position, other than prolonged computer work for data processing, model development, and theoretical calculations.

• Expertise in theoretical chemistry (DFT, QM/MM, molecular dynamics), in developing and using machine learning tools, and in using HPC
• Ability to analyze and interpret complex data, structure a modeling approach, and collaborate effectively within interdisciplinary teams
• Proficiency in Python, experience in code development, or skills in the theoretical study of chemical reactivity will be considered an asset
• Scientific rigor, autonomy, organizational skills, and the ability to successfully complete a research project. Intellectual curiosity, initiative, and the ability to work in a team and communicate scientifically. Adaptability in a dynamic and interdisciplinary research environment
• PhD in theoretical chemistry, computational chemistry or equivalent discipline