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Field
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materials design and theoretical calculations. The project aims to achieve the following goals: Develop a low-temperature macro-preparation technology for hard carbon. Optimize the design of hard carbon
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involve developing an approach that uses Knowledge Organization (KO) metadata and ontologies to optimize parallel processing and scheduling policies (via Kubernetes) for Machine Learning tasks. The fellow
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: • Developing and optimizing DGT passive samplers for simultaneous monitoring of PFAS, antibiotics, and biocides • Designing and conducting laboratory experiments (performance tests, kinetics, microcosms
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous
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strategic plan, including milestones related to data collection, analysis, and reporting. Community Engagement & Translation Develop and execute community engagement strategies, integrating local knowledge
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conduct collaborative research between the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS, https://cosmos.uta.edu/ ) and the Department of Chemistry and Biochemistry (CHEM) on the topic
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to guide the selection of optimal functionalization strategies. Simulating gas adsorption (CO, O₂, H₂, NOₓ, etc.) on ND surfaces to predict binding configurations and IR spectral signatures, enabling
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, simulation and optimization of the phosphate value chain processes. In terms of research, the candidate will reinforce the team of the CBS department. His/her experience and expertise should enable him/her
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, aiming to expand research fields. It includes the theoretical systematization of database aesthetics and the development of case studies to propose solutions that optimize metadata use. Activities involve
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Research or a related field Strong knowledge of quantitative and/or computational research methods, ideally in numerical optimization and simulation models. Proficiency in one of the major programming