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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
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application! Your work assignments The primary focus of this PhD position will consist in generating bioengineered models of human trigeminal pain, implement them in organ-on-a-chip systems emulating trigeminal
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for efficient last-mile deliveries with a focus on climate and flexibility. Using advanced modeling and data analysis, you’ll create solutions that make final deliveries smarter and more sustainable. Your work
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also linked to a broad, interdisciplinary network of researchers in several European countries and in the United States, particularly within experimental studies using cell and animal models, with
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thus continuous aspects, into rule-based models of graph transformation in order to combine the individual strengths of both paradigms. Rule-based models are transparent and explainable; they make sense
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studies using cell and animal models, with the aim of increasing knowledge of the biological mechanisms that may explain epidemiological associations observed in the SELMA study. Link to article Within
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applied statistical models, and will be part of a growing conservation technology hub at the department. The Department of Wildlife, Fish, and Environmental Studies offers a creative, stimulating, and
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process models from the field of spatial statistics to model clustered patterns across the landscape, and develop methods for estimating plant population size and/or change. Qualifications: Requirements
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Physiology and heritable climate adaptation modeling The Swedish University of Agricultural Sciences (SLU)www.slu.se has a key role in the development for sustainable life, based on science and education
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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum