Post-doctorat - Machine learning based MD for two temperature metals - H/F
il y a 2 semaines
Post-doctorat - Machine learning based MD for two temperature metals - H/F Contrat Post-doctorat The advent of femtosecond lasers has shed new light on non-equilibrium physics. The rapid energy absorption by electrons and their subsequent energy transfer to the lattice results in non-equilibrium states of matter, initiating a new class of non-thermal processes from ambient solids to extreme conditions of temperature and pressure. The dynamic interplay between electrons and the atomic structure is the central issue driving ultrafast phase transitions. However, the time scale of phase transitions and the microscopic mechanism driving melting are still not well understood. Classical molecular dynamics is well-suited to address this question, but classical potentials are limited in their ability to describe phenomena induced by electronic structure. DFT-based molecular dynamics could overcome this limitation, but it cannot reach the number of atoms necessary to provide a realistic picture. Machine learning potentials fitted on DFT simulations can bridge this gap. Since a decade Machine Learning Interatomic Potential (MLIP) has proven unprecedented capacities in reproducing DFT reference data for very diverse configurations These potentials rely on defining atomic descriptor that encode the local geometrical environment and then learn the relation between the descriptor and the reference DFT data (energy or atomic forces). This function could be as simple as a linear function or as complex as a multilayer perceptron. As the interation potential between atoms depend on their electronic temperature we propose to learn and incorporate this dependance directly into the MLIP. Then, the Two-Temperature Model, where the diffusion equation for the electronic temperature is solved on a grid and the ionic motion is solved using MD will be employed to investigate out-of-equilibrium effects on the melting dynamics. In particular large scale MD will be used to simulate the melting of a full gold target (few tens of nm length) under laser absorption.The first task for the candidate will be to locate or adapt existing machine learning potentials in the literature to accurately describe metals at high electronic temperatures. This potential will then be fitted on DFT-based simulations and used on simple systems. Then, large-scale molecular dynamics simulations will be conducted on HPC using the molecular dynamics code ExaSTAMP to investigate the time history of a metallic foil illuminated by a femtosecond laser. Throughout the post-doctoral position, the candidate will work in close collaboration with experimental physicists.Conformément aux engagements pris par le CEA en faveur de l'intégration des personnes handicapées, cet emploi est ouvert à toutes et à tous. Le CEA propose des aménagements et/ou des possibilités d'organisation pour l’inclusion des travailleurs handicapés.Participant à la protection nationale, une enquête administrative est réalisée pour tous les collaborateurs du CEA afin d'assurer l'intégrité et la sécurité de la nation. The ideal candidate will have a robust background in either condensed matter physics or plasma physics. Additionally, experience with molecular dynamics simulation is highly desirable. Good skill in programming languages such as C++ and Python is also required.DFT based MD code Abinit, Classical MD code ExaStamp.Post-doctorat #J-18808-Ljbffr
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Internship - Machine Learning for Material Science
il y a 1 semaine
Saclay, France CEA Temps pleinPosition description **Category**: - Mathematics, information, scientific, software **Contract**: - Internship **Job title**: - INTERNSHIP - Machine Learning for Material Science - 6 months - Saclay H/F **Subject**: - Optimization Schemes and Machine Learning for Structural Design Applications in Additive Manufacturing **Contract duration...
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post-doctorat/ingénieur spectrométrie de masse H/F
il y a 2 semaines
Saclay, France CEA Temps pleinpost-doctorat/ingénieur spectrométrie de masse H/F Join to apply for the post-doctorat/ingénieur spectrométrie de masse H/F role at CEA post-doctorat/ingénieur spectrométrie de masse H/F Join to apply for the post-doctorat/ingénieur spectrométrie de masse H/F role at CEA Dans le cadre d’un projet européen, notre laboratoire recherche un...
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Saclay, France CEA Temps pleinDesign of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F Position title: Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F Category: Engineering science Contract type: Internship (6 months) Location: Saclay, Palaiseau, France, Île-de-France Objective:...
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Saclay, France CEA Temps pleinPost-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/FJoin to apply for the Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F role at CEAPost-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F1 day ago Be among the first 25 applicantsJoin to apply for the Post-doctoral Position...
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Post-doctorat : Instrumentation H/F
il y a 6 jours
Saclay, Île-de-France CEA Temps pleinInformations générales Entité de rattachement Le CEA est un acteur majeur de la recherche, au service des citoyens, de l'économie et de l'Etat.Il apporte des solutions concrètes à leurs besoins dans quatre domaines principaux : transition énergétique, transition numérique, technologies pour la médecine du futur, défense et sécurité sur un...
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Saclay, France CEA Temps pleinLearning to focus: Physics‑Informed Deep Learning for Super‑Resolved Ultrasonic Phased-Array Imaging H/F 1 week ago – Be among the first 25 applicants. Category Category: Mathematics, information, scientific, software Position description Internship aiming to design a physics‑informed deep learning framework for super‑resolved ultrasonic imaging,...
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Saclay, Île-de-France CEA Temps pleinPosition descriptionCategoryMathematics, information, scientific, softwareContractInternshipJob titleLearning to focus: Physics-Informed Deep Learning for Super-Resolved Ultrasonic Phased-Array Imaging H/FSubjectThe internship aims to design a physics-informed deep learning framework for super-resolved ultrasonic imaging, extending the Total Focusing Method...
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Saclay, Île-de-France CEA Temps pleinThis post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data Sciences, CEA Saclay), the NRX Nanostructures and X-Rays Team at CEA Grenoble, the University of Lorraine, CentraleSupélec, and the European Synchrotron (ESRF). It is jointly supervised by:Aurore Lomet, Research Engineer in AI at LIAD, CEA...
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Saclay, Île-de-France CEA Temps pleinPosition descriptionCategoryEngineering scienceContractInternshipJob titleDesign of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/FSubjectContext: Modern distributed systems (such as cloud and edge computing platforms) rely on orchestration frameworks like Kubernetes or Docker Swarm to manage the deployment...
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Fully Funded Postdoctoral Scientist Position
il y a 2 semaines
Saclay, France CEA Temps pleinDescription du poste **Domaine**: - Physique de l'état condensé, chimie et nanosciences **Contrat**: - Post-doctorat **Intitulé de l'offre**: - FULLY FUNDED POSTDOCTORAL SCIENTIST POSITION - CEA\IRAMIS\LIDYL - ORME DES MERISIERS H/F **Sujet de stage**: **Durée du contrat (en mois)**: - 12 **Description de l'offre**: The Physics at High Intensity...
