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environment. Development of models to diagnose and predict battery performance and ageing. Participation in national and international research projects related with energy storage and its integration in
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development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high risk individuals and groups. The PDRA will translate conceptual
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functioning will be supported by several EU projects (participation to congress etc..). - main mission: He/she will develop a new generation of predictive models incorporating abundance distribution across size
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, we aim to create autonomous “self-driving” microscopes that: build statistical models of biological dynamics in real time predict the most informative next experiment execute it automatically on living
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and proven expertise in leading predictive modeling, data warehousing, and the deployment of self-service reporting tools and dashboards. 5+ years of senior-level management experience leading large
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pathophysiology associated with inflammation will be used. The results obtained will then be integrated into the development of new in silico models for predicting the toxicity properties of the analyzed
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creating a unified data framework for microbial carbon dioxide conversion and establishing a predictive AI modeling. Your profile The candidate is required to have a strong background in AI/machine learning
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engineering for mobility platforms • AI/ML for transportation prediction, system optimization, and environmental/health impact modeling • Deployment of decision-support tools for public-sector clients
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pain, a critical and currently missing component in translational research. These new models are intended to enable accurate prediction of analgesic efficacy and disease-modifying effects of novel
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deep learning models to predict and analyze large-scale orbital capability. - Evaluate and optimize the performance of the models, comparing them with traditional orbital analysis methods. Where to apply