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is home to a consortium of postdoctoral fellows who provide modeling expertise for a wide range of projects as integral members of those research teams. Unit URL https://imci.uidaho.edu/ www.uidaho.edu
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related field. You bring a strong analytical background and experience with optimization models and quantitative analysis methods. Familiarity with urban energy systems, energy infrastructures, or spatial
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enamel, dental mesowear, mandibular morphometry, dental microwear textures) and GIS spatial analysis to explore their ecologies and identify the impact of structuring territorial features. The results will
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interdisciplinary research group dedicated to developing integrated approaches to geospatial systems analysis. Our team pushes the boundaries of how spatial data can be used to tackle today’s pressing environmental
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Assistant Professor in Marine Biology & Ecology - Biomedical Science or Quantitative Systems Ecology
ecologist working in coastal systems, who applies modern approaches in causal inference, experimental ecology, spatial modelling, and data science, including the use of machine learning to produce rigorous
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cutting-edge single-cell, spatial, in vitro, and surgical approaches in multiple model species and in human organoids to investigate the uterine endometrium and maternal-fetal interface, with the goal
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creating positive relationships with internal and external contracts. Responsibilities: -Staff Support: Provide office support for select division staff (Forest Analytics - FANA, Spatial Solutions - SPSO and
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their spatial patterns in varying environmental conditions. The successful candidate will integrate to the research unit « Microbial Oceanography - LOMIC : http://lomic.obs-banyuls.fr » in Banyuls sur mer, and
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ovarian cancer. The laboratory has about 18 members that study ovarian cancer biology. We use a variety of cutting-edge methods, including spatial proteomics, spatial metabolomics, 3D organotypic cultures
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imaging, spatial data analysis, and machine learning. One arm of the project will seek to engineer diverse quantitative features (e.g., adapting concepts and metrics from network science [5] to characterise