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charging strategies for lithium-ion batteries. The goal is to integrate model-based (digital twin) and data-driven (AI) methods to design and experimentally validate optimized pulse charging protocols. A
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, numerical weather prediction, regional climate modeling, computational fluid dynamics, computer programming, high performance computing, data analysis, and technical writing; ability to work and communicate
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). The institute also maintains locations in Dedelow and Paulinenaue. The position will be based in the Research Platform “Data Analysis and Simulation“ within the Working Group “Ecosystem Modelling“ under
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Materials Research Center (SusMat-RC) at UM6P. The successful candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models
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. LanguagesENGLISHLevelGood Research FieldChemistryYears of Research Experience4 - 10 Additional Information Benefits We offer a post-doctoral position (full-time employment) in the Institute of Physical Chemistry PAS with a
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3 Dec 2025 Job Information Organisation/Company Universite de Montpellier Department Human Resources Research Field Chemistry » Biochemistry Physics » Biophysics Chemistry » Computational chemistry
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hyperparameter optimization and conformal prediction methods; The online monitoring of model reliability and performance indicators in dynamically changing environments; The integration of synthetic data from
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language processing and computer vision reveal the even greater potential of general-purpose foundation models. These models, pre-trained by SSL on diverse datasets and fine-tuned for specific tasks, offer superior
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modeling approaches. • Investigate interactions between food products and paper-based packaging materials across diverse product categories. • Collect, process, and analyze experimental data, including
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will