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pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental
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6 Mar 2026 Job Information Organisation/Company CNRS Department Institut de planétologie et d'astrophysique de Grenoble Research Field Chemistry Physics Technology Researcher Profile Recognised
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workflows to accelerate the discovery and optimization of advanced materials for energy applications. Within the SEMS group at IREC, the main objective is the implementation of an automated experimental
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Postdoctoral position (M/F) on impedance and dielectric study of solid/solid interfaces in batteries
2 Apr 2026 Job Information Organisation/Company CNRS Department Institut de Chimie Moléculaire et des Matériaux d'Orsay Research Field Chemistry Physics Technology Researcher Profile Recognised
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 12 days ago
the interpretability, generalization, and physical consistency of machine learning models for PDEs. Exploring how data-driven methods can accelerate simulations and improve prediction in complex turbulent systems. Your
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and analysis methods for realistic CO2 electrocatalysis, with a focus on parallel investigations and accelerated aging. Dissect degradation processes of CO2 electroreduction catalyst, electrodes, and
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, Experimental Particle Physics - CLASSE The Cornell Laboratory for Accelerator-based Sciences and Education (CLASSE) at Cornell University has an opening for a Postdoctoral Associate to work on the CMS experiment
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Senior Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● Doctoral Degree (or foreign equivalent) in Physics, Computer Science, Computational Neuroscience
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the benefits of HOFI channels for laser wakefield acceleration (LWFA). Your mission will involve applying multi-physics approaches to address both the long time scales required for channel formation and the
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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform