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arrays) from experimental data, leveraging training on simulated datasets. Interpretable neural networks for physics: Development of interpretable deep learning models for identification of matter phases
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to advancing innovative solutions for vibration and noise control in lightweight structures (https://cordis.europa.eu/project/id/101227712 ). The project focuses on the development of Acoustic Black Hole (ABH
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”) on the development of material flow analysis (MFA) methods and digital methods for spatial analysis. Specific tasks comprise: Design and apply digital models for analyzing and simulating circular futures
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to sectors such as Geographic Information Systems (GIS), mobility management, the Internet of Things (IoT), and industrial sensorization. Tasks will include: Definition of reusable models and components
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learning workflows, and developing complete models. Example applications include drug design, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics
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records from stalagmites which grew in coastal caves, to reconstruct the phasing of changes in the North Atlantic salinity relative to AMOC variations, and interpreting them with the aid of process models
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extensive electromagnetic modeling to optimize the waveguide structures for minimal loss, efficient confinement, and effective mode matching with external optical components. Particular attention will be
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statistical modeling, data visualization, and effective communication. The Research Analyst II partners with campus stakeholders to define analytical needs, ensures data integrity through validation and
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statistics, policies, and procedures related to campus safety. Go here to review: https://safety.temple.edu/reports-logs/annual-security-report You may request a copy of the report by calling Temple
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of celestial sources observable with XRISM, simulations of potential XRISM observations, relevant laboratory astrophysics, development of spectral models or atomic codes, or exploring synergies between XRISM and