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physically based framework for interpreting satellite microwave vegetation optical depth (VOD) as an indicator of vegetation water content, biomass, and forest structure. In this position, the
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
(e.g., DeepONet, Fourier Neural Operators) Knowledge of uncertainty quantification, inverse problems, Bayesian inference, or parameter identification In addition you have: A high degree of initiative and
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pipeline. Therefore, you will investigate different types of predictions like intent prediction, reachability approaches or Bayesian filtering and develop a robust prediction algorithm. These dynamic
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develops a physically based framework for interpreting satellite microwave vegetation optical depth (VOD) as an indicator of vegetation water content, biomass, and forest structure. In this position
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The research in this doctoral opportunity will analytical and numerically model the changes in modal responses of a structure under thermo-mechanical loads. Sub-surface fatigue in mechanical
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controlled twist, or when a periodic pattern is imprinted into them, an artificial superlattice emerges in which the band structure can be reshaped and bandgaps opened by design, using a novel
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Job Description Are you passionate about dairy processing, food structure design and clean-label innovation? Join a collaborative PhD project at DTU National Food Institute in partnership with Arla
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undergoing large-scale and unprecedented changes in terms of structure and species composition due to anthropogenic disturbances, climate change, and other global change drivers. Climate, disturbances and
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Job Description Join a research environment focused on developing next-generation computational methods for molecular systems where standard electronic-structure approaches reach their limits. Many
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, Bayesian optimisation, world models and neural simulation. These methods will be used to develop an AI-augmented framework that can translate an artist-led brief into an executable build script