4 Apr 2026
Job Information
- Organisation/Company
CNRS- Department
Laboratoire de physique de la matière condensée- Research Field
Physics
Chemistry » Computational chemistry- Researcher Profile
First Stage Researcher (R1)- Application Deadline
24 Apr 2026 - 23:59 (UTC)- Country
France- Type of Contract
Temporary- Job Status
Full-time- Hours Per Week
35- Offer Starting Date
1 Oct 2026- 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
Offer Description
PMC is one of 22 laboratories located at the Ecole polytechnique research centre working on the frontier of knowledge on the major interdisciplinary scientific, technological and societal issues.
Within the Teaching and Research Department of Ecole polytechnique, PMC (Laboratoire de Physique de la Matière Condensée) is a mixed research unit (Ecole polytechnique/CNRS) whose work is organized around two fundamental topics that are the nanosciences and the physics of Irregularity.
We try to understand the solid, liquid or intermediate states (gel, pastes, foams…)of matter (structure, properties, phenomena of sets related to the interactions between the particles that compose it), the condensed matter physics is a science that is upstream of innumerable technological advances.
The Ph.D. candidate will be enrolled in the doctoral school of Institut Polytechnique de Paris, which hosts about 900 Ph.D. candidates from 30 laboratories and multiple disciplines. In addition to the scientific program, the doctoral school offers general training in soft skills. At PMC, the student will work in the “physics of irregularity” team, at IJL in the “solidification” team.
The thesis is a part of the LUMEN (Liquid structure Understanding for Microstructure Engineering with Novel upscaling assisted by artificial intelligence) project financed by PEPR DIADEM (a public funding program on the development of innovative materials using artificial intelligence). The relevant physical parameters, namely the anisotropies and the diffusion coefficients, will be obtained from molecular dynamics calculations in collaboration with Science et Ingénierie, Matériaux, Procédés (SIMAP) institute, Grenoble. The process parameters will be calibrated on the experimental ones obtained at Institut Jean Lamour (IJL), Nancy. The thesis results will allow to calibrate simulations at the meso- and macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie et l'Environnement (LAMBE), Evry.
The eco-design of novel aluminium (Al) alloys from recycled materials by means of innovative processes such as additive manufacturing plays a key role in the ecological transition. The targeted novel alloys must tolerate the presence of impurities, mostly transition elements (TE) (Fe, Cr, Mn…) encountered in scraps, while preserving high mechanical strength. The addition of TE in small amounts to aluminum alloys can lead to substantial modification of their microstructures. Such solutes promote Icosahedral Short-Range Order (ISRO) in the melt. The ISRO modifies the atom attachment kinetics and plays a role in the selection of the crystallographic orientation of dendrite growth. Consequently, the pattern formation is controlled by the competition between (1) the solute diffusion in the Short-Range-Ordered liquid, (2) the anisotropy of surface energy (an intrinsic property of materials), and (3) the anisotropy of attachment kinetics. The thesis aims at understanding the interplay between the above physical effects on the microstructure evolution of Al alloys during additive manufacturing using the phase-field method. The PhD student will use an in-house phase-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis.
Where to apply
- Website
- https://emploi.cnrs.fr/Offres/Doctorant/UMR7643-ANNDUJ-013/Default.aspx
Requirements
- Research Field
- Physics
- Education Level
- PhD or equivalent
- Research Field
- Chemistry
- Education Level
- PhD or equivalent
- Languages
- FRENCH
- Level
- Basic
- Research Field
- Physics
- Years of Research Experience
- None
- Research Field
- Chemistry » Computational chemistry
- Years of Research Experience
- None
Additional Information
Additional comments
The candidate should hold a master in physics, materials science, or applied mathematics. Previous experience with the numerical solution of partial differential equations is mandatory. The post requires sound knowledge of statistical physics, thermodynamics of irreversible processes, and microstructure formation. Experience on high-performance computing would be a plus. In addition, a high level of communication skills, both oral and written (English required, French optional) is required to be able to present at conferences and write articles in scientific publications. We are looking for a PhD fellow who wants to become fully involved with the project, with a thirst for knowledge, a certain independence of thought and strong motivation to develop new skills in NN in the field of articifical intelligence applied to materials research. In addition, the candidate must be able to work in a team on multi-disciplinary projects.
Applications must include a detailed resume; at least two references (people who may be contracted); a cover letter of one page; a one-page résumé of the dissertation for the master; grades for the master 1 or 2 or the engigneering degree.
- Website for additional job details
https://emploi.cnrs.fr/Offres/Doctorant/UMR7643-ANNDUJ-013/Default.aspx
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Laboratoire de physique de la matière condensée
- Country
- France
- City
- PALAISEAU
- Geofield
Contact
- City
PALAISEAU- Website
http://pmc.polytechnique.fr/
STATUS: EXPIRED
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