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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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Fluid Dynamics simulation code developed by our Project Partners at the Barcelona Supercomputing Center. The PDRA will improve and validate an existing model we have developed to simulate analogue dyke
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machine learning techniques for building efficient reduced-order models in the context of the numerical simulation of parameterized partial differential equations. The analysis of recent deep learning
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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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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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”) 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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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
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. This technology is being developed principally for space applications, but we are also using this to support a vigorous program in laboratory astrophysics using an electron beam ion trap to simulate astrophysical
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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