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Field
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range of molecular systems, including: Transition-metal complexes (e.g., chiral ruthenium and iridium complexes) Local and nonlocal inner-shell decay processes in solvated ions and transition-metal
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join our research activities focused on the development and long-term durability of SOEC cells, with particular emphasis on operation under technologically relevant conditions. Electrolysis and green
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. The project develops process-explicit, hierarchical models that capture key ecological dynamics, integrate diverse and incomplete data sources, and account for uncertainty in ways that are relevant to real
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productivity while reducing external inputs. In parallel, the lab is expanding efforts to understand microbiome-associated phenotypes that contribute to drought tolerance and soil water retention. This includes
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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optical probes on micro-photonic chips for submicron-scale optogenetics, the development of a neuron–computer interface system, and the use of iPSC-derived human neurons for all-optical physiology
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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will unite ecology, statistics, and philosophy to improve the modeling and governance of biodiversity under uncertainty. The project develops process-explicit, hierarchical models that capture key
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parallel testing facilities for companion dogs and children, including equipment for eye-tracking, thermal imaging, touch screen studies, behavioral analysis from video. There is also the possibility