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to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi-modal data into interpretable, scalable prediction and advising models. ICARUS
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
different scales, with the aim to improve our understanding ofthe role of snow in the climate system. Within our Snow Physics group, we are looking for a Postdoc in "Improving understanding & model
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photogrammetric acquisition and reconstruction tailored to GLAM (Galleries, Libraries, Archives, Museums) contexts. Contributing to data registration and deconvolution, metadata acquisition, and high-fidelity model
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iterative validation. The project combines the generalization capabilities of large language models with symbolic constraints and formal verification backends to ensure generated properties are auditable
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mitigation strategies, such as selective yaw control and power down-regulation of wind turbines. Use experimental, field, and numerical data to validate, improve, and develop fast analytical wake models
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quantities that enter ab-initio QT simulations of nanoelectronic devices. In this context, we are seeking a post-doctoral fellow who will be part of a team that also comprises two PhD students and will closely
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models. Building on our preliminary work using retrograde tracing and live-cell imaging to map GB-neuron connectivity, we aim to identify molecular targets for therapeutic intervention. Job description As
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that bridge quantitative modeling and qualitative approaches. Postdoctoral researcher in peri-urban energy planning and sufficiency Your tasks Develop and apply optimization and simulation models to assess
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of the research initiative. In addition, you will have opportunities to develop e large collaborative projects with forest network partners, including members of the ForestPlots network. You hold a PhD in forest
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modelling, molecular engineering, manufacturing and marketing. For HydroCow, we are building on an earlier developed ultra-high-throughput screening platform that allows for the rapid identifying of improved