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dynamical systems theory, including differential equations, simulation techniques, state-space and input-output representations, time-delay embedding, and/or time series analysis from experimental data
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Department of Ecology We are looking for a postdoc/researcher to develop and implement tools for analysis of output from Bayesian inference under phylogenetic models About the position A postdoc
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To fully benefit from automated vehicles (AVs), they must be both safe and appreciated by drivers. This post-doc is to use modeling (e.g., AI/machine learning) and behavior data to predict perceived
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methodologies, tissue analysis with histopathological techniques, and work with genetically engineered mouse models of cancer. Previous experience of conducting and analyzing experiments utilizing single cell RNA
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-of-the-art cell and tumor biology methodologies, tissue analysis with histopathological techniques, and work with genetically engineered mouse models of cancer. Previous experience of conducting and analyzing
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are looking for candidates with a PhD in Computer Science, Visualization and Media Technology, Machine Learning or a closely related research field. A strong background in machine learning and visual data
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, medical analysis and treatment, material processing, etc. You will be given the opportunity to work in one of the world-leading groups in the area and combine device characterization with simulations
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experiments as well as data analysis and interpretation. Example experimental modalities include nano-tomography and scattering experiments at various length scales. The goal is to uncover structure property
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The candidate must have a PhD degree in silviculture and/or forest management or a very similar subject. The candidate must have proven experience in data analysis of tree and stand data, described in scientific
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group within a few years of their PhD. We offer generous funding for up to 9 years, conditional upon favorable review after four years. Data-driven epidemiology and biology of infection covers research