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• Experience in flow cytometry Job Description: This position seeks a highly motivated postdoctoral fellow to investigate how cell death sensors regulate immune responses, with an emerging interest in the retina
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Rasch tables using time calibrations, and documenting and manualizing the algorithms and related products. The post-doctoral associate will be part time, 12-month employee of the University of Minnesota
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analyzing precision agriculture trials integrating UAV, multispectral, and hyperspectral imagery, and ground-based sensor data - A proven ability to develop and maintain effective working relationships and
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a particular focus on the contraction phase of T cell responses. This position seeks to elucidate how innate immune sensors detect dying T cells, and how this process influences the resolution
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sampling), biogeochemical/physical process-based model, advanced AI algorithms, and top-down atmospheric inversions. Tasks Include: Developing AI-ready benchmark datasets to aid in the AI algorithms
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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or education Familiarity with Qualtrics and Inquisit for data collection Proficiency with data pipeline management, including cleaning and coding algorithms (e.g., Python) Familiarity with psychometric analyses