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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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of Process and Materials Sciences, CNRS LSPM UPR3407, on the Villetaneuse campus (Sorbonne Paris Nord University). The postdoctoral researcher will be integrated into the PPANAM (Plasma Processes
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26 Jan 2026 Job Information Organisation/Company CNRS Department Laboratoire de Physique des Solides Research Field Physics Physics » Solid state physics Physics » Surface physics Researcher Profile First Stage Researcher (R1) Application Deadline 16 Feb 2026 - 23:59 (UTC) Country France Type of...
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of physics, materials science, and functional devices. The research will be conducted within the multidisciplinary MNC team, which develops advanced experimental approaches for the study of optoelectronic
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of the nuclear fuel cycle • Knowledge of uranium and fluorine chemistry • Ability to use multiple material characterization techniques (XRD, NMR, EPR, IR and Raman spectroscopies…) • Intellectual rigor and
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electrogravimetric response. To do this, we will implement a multi-stage approach, combining the development of model electroactive materials, their physico-chemical characterisation, and the advanced exploitation
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-dimensional (2D) materials of type MX2 (M=Metal, X=Chalcogen, type WS2, WSe2) and MX (InSe, In2Se3). The scientific aim is to understand the interactions between these different materials according
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nickelocene molecule. They will implement advanced tunneling spectroscopy techniques to probe local exchange interactions and analyze surface magnetic states in ultrathin materials. Only candidates who have
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on simulating nanoalloy structures to create a database for materials characterization. The main tasks include running molecular dynamics and Monte Carlo simulations to model nanoalloys under various
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protocol, critical evaluation of the performance of the pXRF including the evaluation of raw spectra to obtain quantitative chemical data. Explore colour generation based on compositional data, optical