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Field
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learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data
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independent researc A solid background in batteries, battery management systems, battery SoX modeling, thermal management of batteries, battery lifetime estimation and development of experimental setups
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PostDoc in aerobiological modelling Are you interested in atmospheric science and can you contribute to the development of a new generation of numerical models describing concentrations and
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, implementation of management treatments, and the use of coding and process-based models to analyze natural resource dynamics. Learning Objectives: Under the guidance of a mentor, you will build experience in plant
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The Applied Mathematics and Computational Research Division at Lawrence Berkeley National Laboratory (Berkeley Lab) is seeking a Postdoctoral Researcher – Scientific Machine Learning & Computational
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equations, numerical analysis, mathematicalmodels in biomedicine, biostatistics, machine learning, statistical learning, multivariate statistics, time series,mathematical modelling, generalized linear models
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. The postdoctoral scholar will contribute to an exciting research program within the Foy Lab (www.foylab.xyz/) https://foylab.xyz/ , developing machine learning, computational, and mathematical models for improving
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of metamaterial-based supports in attenuating vibrations of the single beam/coupled beam/metabeam systems. • Development of the mathematical models of the single beam/coupled beam/metabeam systems under
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) and contribute to LU-PCG’s research under the U.S. Department of Energy’s (DOE) GENESIS Mission. Research will involve developing fast neural surrogate models, state estimators/virtual sensors, multi
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models