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Field
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at the field, drone, and satellite scale. Big data analysis including processing and analyzing EMIT hyperspectral datacubes over large spatial domains such as the Colorado Plateau and even global. Presenting
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-based models, and remote sensing technologies. Required Qualifications • Ph.D. in Civil or Environmental Engineering, Hydrology, Data Science, Geosciences, Computer Science, or a related field. PhD must
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, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific literature). Our
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. Analyzes large data sets. Analyzes next generation sequencing data (e.g., RNS-seq, whole genome/exome sequencing). Uses state-of-the-art bioinformatical and statistical tools. Develops new statistical
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research projects in their field of expertise. • Assists with the preparation and cleaning of worksite. • Analyzes research data and summarizes results. • Writes and may contribute to research papers
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approaches and big data analysis will be included. As a component of this, it includes data analysis, prepare data for presentations (oral and written), write manuscripts, contribute to grant application, and
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, experimental studies (in vitro and in vivo), and advanced multiomics data science. We are looking for candidates with expertise or interest in environmental health, biostatistics, and data science, especially as
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data from social network surveys, carrying out interviews with participants, and preparing and delivering manuscripts and academic presentations. This position will also mentor graduate and/or
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(CHX, 11-ID) beamline at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced
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from human blood and tissues) and analysis of -omics data, including spatial transcriptomics, to investigate the role of CD8 T cells in the cellular and molecular mechanisms of autoimmune diseases