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with mouse models of neurodegenerative diseases, demyelinating conditions, and brain tumors • Expertise in flow cytometry, including high-dimensional (spectral) flow cytometry for immune phenotyping
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-tuning DNA sequence/genomic/omic large language models (gLLMs) with their applications to genetics, e.g. in identifying causal genes for Alzheimer’s disease (AD). You will have access to state-of-the-art
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mechanisms • Extensive hands-on experience with murine models of liver injury, fibrosis, and regeneration, including tissue dissection and downstream analysis • Proficient in flow cytometry, including high
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expertise in T cell and dendritic cell biology • Extensive hands-on experience with mouse models of infection, inflammation, and immune memory • Proficient in flow cytometry, including high-dimensional and
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working with preclinical models • Experience in one or more of following methods: in vivo behavior, small animal surgery, RNA, DNA, protein extraction and measurement, cell culture, histology
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The research will focus on hybrid AI modeling and agroecosystem sustainability, in collaboration with the AI-CLIMATE
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statistical methods to agronomic research, including mixed models, geospatial statistics, multivariate analysis, and machine learning - Must possess and maintain an active and valid driver’s license Preferred
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, implement, and evaluate computational models that assimilate 2-photon data (60%) Use a computer programming language to create novel neural network simulations (models) that include realistic simulations
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researcher for a 2-year, collaborative project funded by Minnesota’s LCCMR Program titled "Climate change and management effects on lake methane". The position will be based at the University of Minnesota
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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied