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Field
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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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. Specifically, the project will: Address a fundamental knowledge gap about how chromatin 3D organization determines transcription at a global scale in an explicitly defined neuronal development model. Integrate
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computational power and the increasing availability of large volumes of remote sensing data with finer spatial and temporal resolutions have significantly transformed the way we approach climate and weather
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‐based visualization and user-interaction interfaces, including 3D modelling, physics integration, and cross-platform deployment (PC, mobile, AR); integrating and deploying AR navigation applications
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, various cutting-edge experimental and computational approaches in the areas of functional genomics, cell biology, biochemistry, single-cell/spatial multi-omics, data mining, drug screening, and disease
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augmentation for soil and biomass carbon forecasts and scenario modelling across Europe; developing and benchmarking uncertainty quantification methods for space-time predictions and for spatial blocks
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terrestrial gravimetry (measurements, processing, modelling) is an advantage - Understanding of geodetic data analysis and geophysical processes is an asset - Basis understanding of quantum physics is a plus
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will work with data collected from the field to the spatial scale, and investigate spatial optimization approaches to improve the model parameterization at the spatial scale. We expect that you will be
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: Implement and adapt video transformer architectures for sign language processing Spatial Grammar Modeling: Create techniques to represent 3D spatial grammar unique to sign languages Domain Adaptation: Apply