Art à France

Organisation/Company CNRS Department Laboratoire pour l'utilisation des lasers intenses Research Field Physics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 27 Jun 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Sep 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

The Centre Nationale de la Recherche Scientifique (CNRS) is a major player in fundamental research on a global scale. The CNRS is divided into 17 delegations, including the Ile-de-France Gif-sur-Yvette delegation, which is responsible for the Laboratoire pour l'Utilisation des Lasers Intenses (LULI). LULI is based on the École Polytechnique campus, but also has a two further sites, i.e., the Orme des Merisiers site and at Jussieu.

LULI is a research facility with experimental installations (LULI2000 and APOLLON) on two different sites. The laboratory employs around 110 people (researchers, technicians, administrative staff, PhD students).
At LULI, the recruited person will be part of the PHYDHEL team a, which is part of Ecole Polytechnique and Sorbonne University. The thesis will involve close collaboration with our collaborators at the University of Rostock (Germany) and CEA (France). The project will involve experimental campaigns at the LULI2000 facilities that have already been accepted and will be scheduled within the first year of the PhD thesis. The project is associated with a GENCI computational time allocation at the HPC centeres TGCC and CINES, which will be renewed annually. Additionally, a local cluster for test calculations is available.

The position is located in a sector covered by the protection of scientific and technical potential (PPST), and therefore requires, in accordance with the regulations, that your arrival be authorised by the competent authority.

This PhD project focuses on first-principles simulations of hydrogen-helium (H/He) mixtures and their extensions to more complex planetary fluids under extreme pressure-temperature (P–T) conditions, such as those found in the interiors of Jupiter, Saturn, and Uranus. The overarching aim is to provide fundamental insights into H/He demixing, electronic transport properties, and trace element behavior, using a combination of density functional theory molecular dynamics (DFT-MD) and machine learning potentials (MLPs).
The research will begin by studying how hydrogen and helium behave in these extreme environments, especially how they may phase separate at different thermodynamic conditions. These processes are believed to play a key role in shaping the internal structure, magnetic fields, and long-term evolution of gas giants. The student will use powerful simulation tools to model this behavior, including recent machine learning techniques that help extend the range and speed of the calculations.
In a second phase, the focus will shift to investigating how trace elements like neon move through these mixtures. This part of the project will help clarify why some elements appear to be missing from the outer layers of planets like Jupiter—a long-standing question in planetary science.
Finally, the project will expand to include water in the mixtures, allowing the student to simulate more realistic planetary materials. These simulations will help predict how the presence of water changes key properties such as electrical conductivity and reflectivity—both important for understanding observations from space missions and telescopes.
Throughout the PhD, the student will gain experience with state-of-the-art computational tools and contribute to the broader understanding of the physical processes that govern giant planets. The results will support ongoing efforts to build more accurate models of planetary interiors and interpret data from current and future planetary exploration missions.

The activities of the person recruited will be :
-Set up and carry out DFT-MD simulations in an HPC environment.
-Implement new simulation data analysis tools.
-Analyze, organize and visualize data.
-Close collaboration with experimental and planetary interior modeling colleagues. Summarize and present results at group meetings and conferences.
-Prepare results for publication and put them into context with literature data.

The candidate should have a background in high-pressure physics/chemistry, plasma physics, material science or engineering. Prior knowledge of density functional theory and/or the basics of molecular dynamics is crucial for the project. We especially value candidates with experience in performing DFT-MD simulations with VASP or Abinit or MD simulations with LAMMPS in a HPC environment. Additional knowledge of machine learning potentials, free-energy calculations or structure prediction is a plus. The candidate should have experience with programming and data analysis (e.g. python, C/C++, ...). Strong communication skills are greatly appreciated. The person to be recruited must be able to work in a team, as well as independently. The candidate must be able to draft documents and report back. A good command of English is a plus.

Interested candidates should send a motivation letter and a detailed CV including the email addresses of two references that can provide reference letters.