Missions

The postdoctoral fellow will participate in the PostGenAI@Paris AI Cluster (ANR) project at Sorbonne University, and more specifically in the "AI-Augmented Multiscale Modeling for Energy Storage" sub-project, whose objective is to develop artificial intelligence methods that complement modeling techniques, particularly at the atomic scale, specific to the physical chemistry of materials.

In this context, the postdoctoral fellow will seek to elucidate the fundamental processes leading to the formation of the "Solid Electrolyte Interphase" (SEI) in batteries. This will include understanding the precipitation of species formed on the electrode surface by electrolyte degradation, using molecular simulations. To this end, the postdoctoral fellow will develop methods to sample and characterize these processes using machine learning tools.

Activités

The postdoctoral fellow will contribute to various aspects of the project, such as:
* developing new theoretical and numerical approaches for determining the thermodynamic and kinetic properties associated with a transformation, using artificial intelligence tools
* performing molecular dynamics simulations
* developing codes to analyze these simulations, using existing laboratory tools
* collaborating with other project participants
* writing publications and participating in conferences

Compétences

* Skills/knowledge: statistical physics, physical chemistry, machine learning
* Expertise: molecular simulations, programming experience (Python, C++, Julia, C, etc.), Python programming for artificial intelligence (Pytorch, TensorFlow, etc.)
* Soft skills: teamwork

Contexte de travail

The PHENIX laboratory (Physicalchemistry of Electrolytes and Interfacial Nanosystems) is a Joint Research Unit between the CNRS and Sorbonne University. It is located on the Pierre and Marie Curie campus in central Paris. It comprises approximately 90-100 researchers, lecturers, doctoral students, and postdoctoral fellows, and conducts research in the fields of energy (electrochemical storage, recycling, etc.), health (nanoparticles for imaging, etc.), and the environment (waste storage, water treatment, etc.).

The postdoctoral fellow will be part of the Multiscale Modeling and Experiments team and will conduct their research as part of the PostGenAI@Paris project, in collaboration with the IMPMC laboratory (Institute of Mineralogy, Materials Physics, and Cosmochemistry), located on the same campus. They will have access to the laboratory's and university's computing resources.