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Field
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15 Jan 2026 Job Information Organisation/Company CNRS Department Laboratoire national des champs magnétiques intenses Research Field Physics » Condensed matter properties Physics » Solid state
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frameworks and methods such as 1D-CNNs, transformers, or chemometrics for spectral analysis is highly valued, though applicants with strong backgrounds in physics, physical chemistry, or analytical chemistry
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complexes involved in the molecular mechanism of cyclic electron flow (CEF) in cyanobacteria. The position is embedded within a large national project PHOTOMACHINES (2024–2028), focused on the development
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Additive Manufacturing (AM) enables unprecedented design freedom for next-generation thermal management systems, particularly through the fabrication of mini- and micro-channels with complex internal
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-of-cellular-metabolism/ The position is for you if: …you have strong data analysis skills and enjoy working with large, complex datasets (e.g., single-cell, spatial, imaging-based or other omics data) …you have
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involved in the Trusted Autonomous and Self-Adaptive Systems for Defence (SAACD) project. This project aims to overhaul the engineering and development of this type of complex system. A SAACD can be defined
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for candidates with interests in multiscale simulations of complex physical phenomena, from the atomistic/electronic scale to mesocopics and beyond. Of particular interest is the development and application
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by prof. Vittorio Murino. Specifically, AIGO research is centered on the development of advanced machine learning and deep learning methodologies for learning from complex, multimodal, and imperfect
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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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physics, topological states of matter, and spintronics. The position includes collaboration with the Dahlem Center for Complex Quantum Systems (DCCQS). The position serves to further the candidate's own