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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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systems, GHG emissions, waste and/or sludge management from SMEs/SMEs.• Experience with Python for data analysis, model automation and spatial/environmental processing.• Previous experience in research
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on spatial reasoning, semantic technologies and AI for geosciences. Where to apply Website https://www.academictransfer.com/en/jobs/356999/phd-semantic-modelling-of-geoda… Requirements Specific Requirements A
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spatial point process models for the emergence and arrangement of objects (including birth-death dynamics, merging, and non-overlap constraints) with methods from shape analysis, in particular stochastic
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. The project involves large-scale analysis of high-dimensional datasets, including: single-cell and single-nucleus RNA sequencing spatial transcriptomics (e.g., 10x Genomics, Xenium) germline and somatic
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to the arrival of PLATO observations. The PhD will initially focus on the analysis and modelling of spectropolarimetric data to characterise the magnetic fields of the target stars. From mid-2027 onwards
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technologies, spatial omics data, immunology and cancer systems biology. Experience with genomic engineering methods, stem cell culture, flow cytometry, and murine models is preferred. Ability to work
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an important entry point for data and models in the Metropolitan Region of Amsterdam. Where to apply Website https://www.academictransfer.com/en/jobs/357691/postdoc-micromacro-modelling
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investigations, and modelling. The project focuses on spatially and temporally resolved infiltration processes and examines how rainfall characteristics and seasonal variability (e.g. freeze–thaw cycles and