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research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for spatial population
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identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See https://equity.unl.edu/notice-nondiscrimination/ . Minimum Required Qualifications
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genomics is considered an advantage Understanding metastatic potential and tumor immunobiology at the single cell and spatial level In this project we use all-things-omics, with short and long read
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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | about 1 month ago
corresponds to a land occupation pattern characterized by isolated and discontinuous constructions in a predominantly rural or peri-urban territory, resulting in low density and spatial fragmentation
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the molten salt NaAlCl4 electrolyte chemistry by among others in situ Raman probe spectroscopy to investigate spatially resolved compositional changes during charging/discharging of the battery, and
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of visual texts and will focus on the semiotic analysis of the design dimension,whether artistic,design-related,or architectural,with particular reference to the role of corporeality and spatiality and the
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research and applications of advanced spatial data analysis methods, data collection, and interpretation of remote sensing data, database system theory, mapping, spatial data distribution, development of new
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focuses on studying the socio-geographic transformation of society, its conditions, developmental tendencies, and spatial structure - with implications for societal organization and an emphasis
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inflammatory systems; applying cutting-edge multi-omics technologies such as single-cell sequencing and spatial transcriptomics to translational research; and developing novel therapeutic strategies and
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be