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analytical technique. Build an understanding of pharmaceutical dissolution and drug-release principles and learn to evaluate relationships between formulation microstructure, chemical distribution, material
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, hierarchical CGM data under combined missingness and censoring scenarios, extend these methodologies beyond TIR to metrics with distinct distributional characteristics such as time above/below glycemic target
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when these arise. Research Project: The Respiratory Virus Hospitalization Surveillance Network (RESP-NET) Team, within the Surveillance, Epidemiology and Prevention Branch of CORVD, is seeking a
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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well as communicate with research networks within the scientific community. Learning Objectives: As part of this learning experience, you may: Learn how grapevine populations and germplasm are evaluated to identify
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pathology, bioinformatics, comparative evolution and other areas. You will also have opportunities to attend scientific conferences for presenting the research results and establish collaborative networks
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. Additionally, we intend to measure root water uptake using sap flow meters. The data will be integrated using recently developed physics-informed neural networks in order to translate apparent resistivity data
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include acquisition, documentation, maintenance, characterization, breeding, enhancement and distribution of the assigned crops. PGRU maintains approximately 20,000 different accessions, representing over
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training, travel to communicate findings, and professional networking will also be available. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn to: (a) plan, execute
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structures, molecular networks, and disease-resistance phenotypes. Artificial intelligence (AI), machine learning, and bioinformatics will connect genotypes with phenotypes and identify maize and fungal genes