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Field
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and physical modelling. The goal of this position is to develop data-driven approaches to AI-based analysis of complex interaction systems and suitable hybrid architectures for this purpose
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, optogenetic and electrical stimulation, neuromodulation and lesion-based validation, signal processing, computational network analysis, and dissemination of results. The postdoctoral associate will work with
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mission by developing and applying advanced analytical and experimental approaches to address complex interdisciplinary environmental and infrastructure challenges relevant to NH. The postdoc’s work
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) calculations, crystal structure prediction, NMR simulation, scientific programming, or quantitative data analysis. Demonstrated ability to conduct independent research, analyze complex datasets, communicate
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, the fellow will lead the development and execution of advanced functional and distributional data analysis techniques. This role requires independent analytical acumen to design simulation studies, process
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via protein and RNA analysis including histology, immunohistochemistry, cell culture, cellular assays, RT-PCR, Western blot analysis, ELIspot and cellular imaging. Scientist will help use the data
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support applied research projects focused on grazing management and soil health. This position will lead the analysis and interpretation of soil data already collected across multiple projects spanning
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gene expression analysis (qPCR/RNA-based approaches), protein analysis, lipidomics/metabolomics, flow cytometry, or biochemical assays. Demonstrated ability to design and execute hypothesis-driven
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, and PCR techniques. Proven experience using bioinformatic pipelines to analyze and visualize complex biological/genomic datasets. Demonstrated background in grant writing (e.g., NIH, NSF, private
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-omics data integration, statistical analysis, and biological interpretation of complex datasets. Demonstrated ability to support collaborative research projects and communicate technical findings