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Institute of Geography and Spatial Organization, Polish Academy of Sciences | Poland | about 15 hours ago
their acquisition, processing, and analysis, knowledge of environmental and spatial data formats (including netCDF, GeoTIFF), proficiency in GIS tools (ArcGIS, QGIS), knowledge of statistical methods and time series
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collaborate with colleagues to perform project tasks and work together with other PhD students in developing spatial modelling approaches Where to apply Website https://www.academictransfer.com/en/jobs/360192
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, or probabilistic modelling. Familiarity with HPC or cloud-based analysis workflows. Experience with immunological datasets or spatial tissue profiling is a plus. We offer: An international cutting-edge research
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in policy and decision-making. In this PhD, you will contribute to a new generation of spatially explicit models and assessments that capture these feedbacks across spatial and temporal scales
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one or a combination of the following: quantitative analysis, modelling, spatial analysis, optimisation, forest restoration, ecosystem services valuation, policy analysis, market design, or
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protected by law. Salary Range: Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines Create a Job
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. We are seeking an energetic and independent researcher who has a strong background in quantitative analysis of social surveys. To qualify for the position, a candidate must have completed a PhD by the
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models, for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics), large textual corpora (e.g., scientific literature), and/or pathologic images. Our research
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Nantes, Pays de la Loire | France | 23 days ago
resources and their ecosystems. The PhD supervisory team brings together complementary expertise in spatial modelling, marine ecology, fisheries science, and maritime spatial planning. Internal collaborations
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biology, single-cell or spatial transcriptomics, bioinformatics, or multi-omic data integration. Experience with endogenous tissue, image analysis, or comparative developmental datasets is an advantage, but