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Field
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from cognitive-behavioural testing (connected to hippocampus-dependent cognitive domains such as learning, memory, and spatial navigation). An essential point will be integrating multifaceted data
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with or managing research activities, and preparing reports. Strong skills in statistical analysis and handling large spatial and temporal datasets. Good communication skills for collaboration within
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. Preferred qualifications ● Fluency in fisheries and/or bioeconomic modeling, with experience in spatial fisheries ecology or management strongly preferred; ● Advanced understanding of the biology and
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energy supply systems, multi-objective and stochastic optimization, advanced statistical analysis, and data visualization. This position offers the opportunity to work with a multidisciplinary team of
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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to help define a new frontier at the interface of spatial biology and therapeutics. The scholar will lead spatial-biology driven projects to identify novel spatial biomarkers, therapeutic targets, and
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-based microarrays, immunohistocheistry, spatial transcriptomics and molecular analysis. The candidate is expected to be able to summarize data for inclusion in grant proposals and manuscripts; prepare
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Analysis for Planning Renewable Energy (MapRE) initiative, a spatial analysis platform for planning renewable energy deployment, and GridPath, an electricity system planning and operations analysis platform
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experiments. Develop and optimize sample preparation protocols including flash freezing/ chemical fixation of samples and cryo-sectioning. Process and analyze complex spatial metabolomics datasets. Lead
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received after the review date will only be considered if the position has not yet been filled. Position description The Spatial Climate Solutions Lab at the University of California, Santa Barbara, is