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macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie
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, resilience and evolution of marine life to develop solid theories and predictive models of the relationships between marine biodiversity and ecosystem functions, which will in turn lead to improved economic
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computational modeling for astronaut risk prediction; & interact with recognized university and industry collaborators. Field of Science: Biological Sciences Advisors: Joshua Alwood Joshua.s.alwood@nasa.gov (650
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to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi-modal data into interpretable, scalable prediction and advising models. ICARUS
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2030 program (see https://www.pepr-risques.fr/fr/programme-de-recherche-risques-irima ). IRIMA is led by CNRS, Grenoble Alpes University and BRGM, and aims to structure and strengthen hazard and risk
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genetics to predict breast cancer risk and tumour aggressiveness in BRCA variant carriers Digital biomarkers for enhanced AI-guided therapy in heart failure (D-BEAT) Experimental models for optimizing
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14 Mar 2026 Job Information Organisation/Company Scuola IMT Alti Studi Lucca Research Field Computer science » Modelling tools Engineering » Control engineering Physics » Applied physics Engineering
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spectroscopy, especially applied to the analysis of lipids or oils. Experience in the application of chemometrics to develop predictive models Participation in competitive research projects related to the field
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on building dynamic system models for both the energy conversion technologies and the greenhouse climate, integrating these into a unified framework suitable for state estimation, predictive control, and
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challenging. The objective of this PhD is to develop a predictive modeling framework that explicitly links multiscale physical mechanisms to macroscopic responses. The work will follow a multiscale and