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group led by Dr. David Klinges in the Department of Ecology, Evolution & Natural Resources. Our work combines computational modeling, field studies, and laboratory experiments to understand how
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. The incumbent will operate at the forefront of translational metabolic research, combining mechanistic rodent studies with state-of-the-art laboratory approaches, including stable isotope tracing and metabolomics
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translated into systemic physiological responses. We combine Drosophila neurogenetics, optogenetics, connectomics analysis, metabolomics, and lipidomics to investigate how these neural signals reshape systemic
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the genomic stability of oocytes and somatic cells exposed to CK2II in combination with cyclophosphamide. This study will perform a comprehensive assessment of DNA damage, including mutation rates, DNA
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of the meiotic cell cycle. Our work involves genetic mouse models, combined with molecular, cellular, and biochemical analyses. A successful candidate will work closely with the principal investigator as
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and analysis, including the development of new techniques and customized pipelines; (2) planet characterization combining space-based observations with ground-based, high-resolution spectroscopy; (3
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combining these tools with theoretical models, we aim to understand how the brain supports thoughts, emotions, and decisions—and how disruptions or biases in these processes impact mental health and addictive
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the state, including combined flooding from sea level rise, storm surge, and inland rainfall, storm-induced extreme winds and precipitation, and sequential synoptic weather systems or predecessor events
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participate in NIH-funded research focused on the discovery and mechanistic characterization of nucleotide-competing inhibitors of HIV-1 and LINE-1 reverse transcriptases (RT). The project combines structural
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combining these tools with theoretical models, we aim to understand how the brain supports thoughts, emotions, and decisions—and how disruptions or biases in these processes impact mental health and addictive