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have access to state-of-the-art facilities, including cleanroom microfabrication, laser micromachining, 3D printing, advanced microscopy, and numerical modeling tools. The project benefits from a close
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physics, biophysics and climate physics. Roughly 30 new doctoral students and postdoctoral researchers join the Laboratory every year. Sea-level projections are derived using Earth-system models (ESM
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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predictive digital twin of the face to better understand, model, and rehabilitate facial expressions. The project is led by the BMBI laboratory (UTC-CNRS) and brings together a multidisciplinary consortium
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requirements for training data, memory, and computing power while maintaining a high level of accuracy. Particular attention will be paid to the explainability and embedding of the models to facilitate
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. The PhD student will be in charge of analyzing the full data set in order to finalize the background model, study the two-neutrino double-beta decay of 82-Se, and search for neutrinoless modes. Where
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, France to complete the project. Objectives The objective of this PhD project is to develop advanced numerical modelling tools to support the digital twins of refractory materials, with the aim
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and experimental models to study metabolic communication in GBM invasion. In this context, spatial transcriptomics and mass spectrometry imaging provide tissue-level maps of tumour–microenvironment
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to the development of energy models; • to access complementary experimental platforms; • to strengthen Franco-Canadian scientific collaborations. The project also benefits from industrial support through
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model of magmatic oceans on forming planets based on laboratory experiments. At present, high-pressure molten silicates are modelled only in a rudimentary manner, due to a lack of data on activity