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. DESIRABLE EXPERIENCE Ecosystem monitoring and vegetation indices. Time-series analysis of environmental or satellite data. Cloud-based geospatial computing and large-scale data synthesis. CONTRACT DETAILS
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scalability studies to identify and improve bottlenecks in large codes. Experience in development of data-driven reduced-order models in one or more of these areas: turbulence, boundary layer flows, combustion
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large amounts of geospatial training data to effectively classify grazing, haying, and other grassland management regimes on U.S. agricultural lands. The researcher will also work closely with colleagues
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of Health (LIH) is seeking a highly motivated Postdoctoral Researcher with specialized expertise in multi-omics data analysis. You will play a central role in analyzing large datasets from multiple large
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performing experiments, analyzing data, contributing to manuscript and grant preparation, and mentoring and training laboratory personnel. Additional training and professional development opportunities aligned
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recognition. Primary Job Responsibilities Determine high‑resolution structures of large enzyme complexes using cryo‑EM (single-particle reconstruction and/or cryo‑EM sample preparation and data collection
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for 3 years and is based in the Big Data Institute, Old Road Campus, Oxford. The post is only available as full-time. However, we can discuss flexible working hours (e.g. starting and finishing earlier in
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/Statistics Internal Number: JR101137_1774276539 The Data Science and Statistics Program at the University of Richmond invites applications for a two-year postdoctoral research position in the Distant Viewing
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. Applicants must have experience in the handling and organization of large data sets. Familiarity with analysis of panel or longitudinal data and working with multilevel models is valued. Additional skills with
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of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single-cell sequencing, gene expression, proteomics, or metabolomics