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diagnosis of gas turbines. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components
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kinetic models and their hydrodynamic limits. Dispersive phenomena in kinetic theory. Quantum gases. Applicants must hold a PhD degree in mathematics, physics or a related field. We seek candidates with
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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Applied to Neuroscience and Drug Discovery Where to apply Website https://gestiononline.bioef.eus/ConvocatoriasPropiasBiobizkaia/es/Convocatorias… Requirements Research FieldOtherEducation LevelPhD
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Posting Summary Logo Posting Number RTF00059PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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Posting Summary Logo Posting Number RTF00059PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly skilled workforce
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. The post will be primarily based at Guy’s Campus. The successful candidate will work closely with Professor James Arnold (https://www.linkedin.com/in/james-arnold-1a0497263/ ) to support and further develop
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Geological Engineering/Geology/Physics - Master's degree in Geological Engineering/Geology/Physics - PhD in Geology/Physics (within max. 5 years of obtaining the doctorate) Where to apply E-mail mihai
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signal-to noise Post-processing: denoising, reconstruction algorithms Comparison with high-field MRI: deep-learning and other AI modalities for low-field MRI optimization Close cooperation with