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Field
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) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness of the assessment. All components assembled
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a given discrete-event model that is safe with respect to certain requirements. Yet, the application of the approach is limited by the fact that tools for synthesis cannot always deal with the state
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(e.g., Kalman Filter) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness
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focus of this position is research on hydrodynamic loads and performance of tidal turbines under realistic flow and clearance conditions. Tidal-stream energy offers a predictable, complementary renewable
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for Nuclear Research (NCBJ) is inviting applications for a position PhD student - scholarship (machine learning-driven modeling of metallic glasses) Location: Otwock - Świerk - in the outskirts of Warsaw with
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improve prognostication in critically ill patients by integrating cardiovascular risk factors into existing ICU prediction models. by combining cutting-edge data science with advanced clinical expertise and
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Predoctoral researcher at the Targeted Therapeutics & Nanodevices Research Group (Project BRAINZYME)
physiological conditions. • Examine their performance in 2D and 3D systems, including chemical and genetic disease models, multi-cultures and organ-on-a-chip devices. • Investigate the biodistribution as
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basic and multiomics data analysis, Flow cytometric analysis of immune cell populations Immunohistological staining and imaging Biochemical assays for cytokines and other inflammatory mediators Protein
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. This will involve investigating techniques for model compression and efficient inference to enable on-board condition monitoring directly at the wind turbine, reducing data transmission requirements, central
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are offering a fully funded PhD position in the field of Physics-informed Learning-based Control. This interdisciplinary research area bridges control theory, machine learning, and physics-based modeling