General information
Offer title : Postdoctoral researcher (M/F) in theoretical chemistry for the prediction of superconducting hydrides using machine learning and DFT calculations (H/F)
Reference : UMR7285-CARNOE-068
Number of position : 1
Workplace : POITIERS
Date of publication : 30 October 2025
Type of Contract : Researcher in FTC
Contract Period : 12 months
Expected date of employment : 1 January 2026
Proportion of work : Full Time
Remuneration : Between €3,041.58 and €3,467.33 gross monthly depending on experience
Desired level of education : Doctorate
Experience required : 1 to 4 years
Section(s) CN : 13 - Physical chemistry, theoretical and analytic
Missions
Recruited by the CNRS, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling of materials.
Activities
The main activities will include:
- formulating new descriptors of critical temperature (Tc) incorporating electronic fluctuation effects, evaluated by conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned Interatomic Potentials) code for ternary compounds with variable composition with crystal structure optimization algorithms (evolutionary, random, etc.);
- Application of the CSP DFT/MLIP methodology to various research problems in chemistry (ANR TcPredictor project) and to the study of materials under pressure, in particular superconducting hydrides; implementation of a multi-objective Tc-energy approach to optimize ternary hydrides and other materials;
- Calculating the electronic structures of configurations generated in silico, as well as their thermodynamic, dynamic (phonon), and mechanical properties, and performing DFT/MLIP molecular dynamics simulations;
- Analyzing and exploiting results, as well as writing activity reports and scientific publications and presenting results at conferences and working groups;
- Installing, maintaining, and monitoring calculation codes on GENCI platforms and the local cluster; implementing Python tools for automating CSP/DFT calculations;
- Participating in the scientific activities of the Applied Quantum Chemistry group (IC2MP) and the ANR consortium (TcPredictor project);
- Supervision of students on research internships.
Skills
- PhD in theoretical chemistry applied to materials, materials physics, or computer science/applied mathematics;
- Solid experience in DFT applied to periodic systems (codes such as CASTEP, VASP, Quantum ESPRESSO, xtb, etc.) and in Machine-Learned Potentials (MLIP) approaches;
- Excellent command of Python programming languages (and ideally C++ or Fortran) as well as the Unix/Linux environment;
- Good command of scientific English, both written and spoken (certified level).
Work Context
The work will be carried out at the CNRS – Institute of Chemistry of Environments and Materials in Poitiers (IC2MP, UMR CNRS 7285), within the Applied Quantum Chemistry group of the Catalysis and Unconventional Environments team (https://ic2mp.labo.univ-poitiers.fr/)
Constraints and risks
Occasional assignments in France and/or abroad possible.