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change. Experience in quantitative methods, spatial analysis, or handling large datasets would be valuable, but full training will be provided in climate modelling, statistical downscaling, and health
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French institution with a research mission PHD Country: France Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/134977 Requirements Specific Requirements We are looking for a
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for single-cell and spatial omics Deep learning and representation learning to model cellular states and interactions Explainable AI for biomarker discovery and patient stratification Cross-disease modeling
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Austrian Academy of Sciences, The Vienna Institute of Demography (VID) | Austria | about 2 months ago
to join the project “Spatio-temporal modelling of family change” (SPATEMO; funded by FWF ), a French-Austrian collaboration between the VID and IDEES (CNRS) . Using a spatio-temporal, empirical and spatial
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, using QUASI observations for validation and pushing the frontier of coupled modeling at submesoscales. Where, how, and with whom you’ll work Both PhDs will join the Geoscience and Remote Sensing
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. Parametric algorithms and ML models trained on simulation-derived and measured datasets will approximate key microclimate variables and associated human–bioclimatic responses across a wide range of spatial and
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the Experiment grant. The candidate must have: A PhD degree in a relevant field (e.g. Molecular Biology, Neuroscience). A proven track record either in spatial transcriptomics or extracellular vesicle biology. The
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areas*; 2. Technical Skills - Experience in processing 3D point clouds (LiDAR or photogrammetry); Knowledge of GIS, remote sensing, or spatial analysis; 3. Research Experience (Preferred) — Previous
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Results: Ability to assess the influence of the engine plume on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion behaviour
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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original