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opportunity to pursue an ambitious research agenda that will drastically advance the state-of-the-art in sparse computations both as a unified topic and within three broad pillars: sparse and structured matrix
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the theoretical and computational mechanics of shell structures, with a focus on extending these models to incorporate coupling with electromagnetic theory. This position is part of an interdisciplinary effort to
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farm-scale modelling of nutrient flows. Food security, climate change and loss of biodiversity represent three of today’s major societal challenges. Finding solutions for all these challenges requires
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design of hyperstable miniprotein binders using advanced computational platforms. The work integrates protein modeling, in silico affinity optimization, and mechanistic studies aimed at modulating key
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on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
research environment and advance knowledge within their fields. Postdocs are crucial members of our scientific research workforce, contributors to our research outputs and an important reason why Carolina is
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statistical analysis and computer programming in any of the following areas are highly valued: structural equation modeling, mixed effects modeling, mediation analysis, spatial modeling, web-based mapping
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health and well-being, cognitive aging and dementia, loneliness and social isolation, and integrative data analysis. Strong analytic skills such as structural equation modeling, multilevel modeling
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and advancing vaccine and therapeutic design for cancer and other diseases that affect both humans and animals. The successful candidate will be involved in the structural analysis of antigens
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-specific findings into conservation and ecosystem restoration to advance outcome success. We test our research questions with multi-factorial, field experiments and complement that approach with modeling