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artificial intelligence and generative modelling, that integrate single-cell genomics and spatial profiling to study cancer evolution, therapy resistance, and immune escape in urologic cancers (especially
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interpretation in support of researchers at the FGCZ. Within that field, the team covers raw data processing, high-performance computing, statistical evaluation, interpretation, and integrated analysis. The unit
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mathematics Mathematics » Computational mathematics Mathematics » Probability theory Mathematics » Statistics Researcher Profile First Stage Researcher (R1) Application Deadline 1 Sep 2026 - 21:59 (UTC) Country
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Area of research: Scientific / postdoctoral posts Job description: Staff scientist (f/m/x) Core Facility Bioinformatics and Statistics 102965 Full time 39 h/week Neuherberg near Munich Partial Home
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feasibility, spatial placement and configuration of NBS and evaluate their performances from a decision support context. The successful applicant must ensure AI and machine learning technologies are well
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and methodologies. Experience analyzing and interpreting spatial datasets using GIS software (e.g., ArcGIS). Experience conducting meta-analyses or applying meta-analytical statistical techniques
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University of California Agriculture and Natural Resources | Davis, California | United States | 2 months ago
, linear and logistic regression, multilevel modeling, causal analyses, spatial analyses, and determines sampling and reporting procedures. Analyzes research data using statistical and geospatial software
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interaction of these fields in terms of theories, methods and techniques, as well as their application via concepts, strategies and spatial interventions, as a significant part of ETD's research portfolio
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University of Gothenburg/Department of Biological and Environmental Science | Sweden | about 1 month ago
processing of sequence data, phylogenomic analysis, GIS-based spatial analysis, and comparative macroevolutionary analysis. Attend local and/or international conferences for the purpose of presenting research
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, filter banks, transforms, and statistical or entropy coding; Development of compression methods tailored to the spatial, temporal, and spectral characteristics of DAS data; Development of algorithms