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emissions due to the large temporal and spatial variations in CH4 emission and its underlying processes. The lack of continuous observations of CH4 turnover hinders our understanding of CH4 emission
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technologies (e.g., spatial transcriptomics, CODEX, Akoya PhenoCycler). Proficiency in single-cell RNA sequencing, high-dimensional data analysis, bioinformatics tools, and programming languages (R, Python
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in physical layer algorithm design and performance analysis Proven track record of publications in relevant IEEE journals and conferences In addition to the above qualifications, it is highly desirable
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behavior. Preferred Qualifications: Experience using quantitative spatial techniques to characterize neuron distribution. Brief Description of Duties: The Postdoctoral Associate will assist the Principal
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of the Mississippi embayment), surface water hydrology and modeling, model coupling, and spatial/temporal data analysis. The successful candidate will work with Dr. Brian Waldron and CAESER faculty/staff on projects
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crust and mantle lithosphere. This covers the entire spectrum of topics ranging from geomechanics and rock physics to the rheology of crust and uppermost mantle, ranging over the entire spatial bandwidth
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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electrophysiology and sleep) and (ii) in spatial transcriptomics and high-resolution imaging. The selected candidate will work at the intersection of molecular biology and systems neuroscience, gaining a unique
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complex endometrial models and optimizing in vitro implantation assays. Culturing human embryos and generating stem cell-based embryo models. Tissue sectioning for advanced spatial transcriptomic analysis