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analysis and statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g
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Information Science (GISc) — particularly in movement analysis — with teaching and student supervision? Have you recently earned a PhD in GISc and feel inspired to share your expertise with the next generation while
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to the Dillon Lab’s multidisciplinary research program evaluating the sustainability of animal-source foods. The position combines spatial analysis, livestock systems modeling, and environmental assessment
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-spatiale proposées, et l'idée de passage entre les soins en structure et au domicile. Le projet ARCADE vise à évaluer la faisabilité et l'efficacité d'un programme de rééducation cognitivo-motrice basé sur
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advancements in spatial bioinformatics. Assist with the epigenetic analysis performed within CIMP and MBH lab. What we offer Opportunity to become a leading-edge expert in spatial bioinformatic, being
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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | about 2 months ago
and ecological change. The research combines critical advanced quantitative spatial analysis with qualitative and participatory approaches to connect structural inequalities with lived experience
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, xenograft models, brain tumor biology, confocal imaging, immunofluorescence and/or FISH and/or computational analysis of scRNAseq/RNAseq/spatial transcriptomics Background in brain tumor biology Knowledge
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the TME are relevant to tumour evolution and patient survival outcomes [2-4]. This PhD project will seek to investigate the prognostic value of spatial immunophenotypes in lung cancer combining high-plex
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leading role at the international level, for example in the field of plant and microbial data management, in the evaluation of new methods of genome analysis, in the integration, interpretation, and
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addition to holding a PhD, you must have a strong analytical background and experience in quantitative ecology, spatial analysis, handling large and complex datasets, and proficiency in programming (e.g., R or Python