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spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint for the construction industry and enable
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complex real-time control challenges under safety constraints. The Postdoccandidate will be responsible to: Conduct literature and technology reviews focusing on real-time embedded control and functional
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and neurophysiology(EMG/EEG). You have extensive data processing experience(Python, Matlab or other platforms), being able to independently conduct complex signal processing and machine learning
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aerosol phase behavior. We will deploy microscopy-based techniques to probe the phase behavior of well characterized particles. Through targeted experiments, complex SOA types will be generated in our
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Postdoc in atmospheric chemistry on investigating the phase behavior of secondary organic aerosol...
aerosol phase behavior. We will deploy microscopy-based techniques to probe the phase behavior of well characterized particles. Through targeted experiments, complex SOA types will be generated in our
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2-yr postdoc on Forecasting Biosphere-Scale Effects of Ecological Novelty Using Species Distribut...
distribution models (SDMs), with a focus on key novelty drivers such as climate warming, rising CO2, and trophic disruptions, while integrating key ecological processes including trophic complexity, disturbance