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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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. 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
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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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inventorying forest biodiversity. Possible areas include: indicators of functional or taxonomic diversity species-specific or habitat-based monitoring combinations of field data, remote sensing, and modelling
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both experimental development and theoretical modelling. Therefore, it requires the candidate to have a solid background in physics, electronics, and mathematics, along with strong practical experimental
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areas include: indicators of functional or taxonomic diversity species-specific or habitat-based monitoring combinations of field data, remote sensing, and modelling new techniques for detecting and
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electrification of the broader economy affect the competitiveness of power producers via a Nash-Cournot model of regional energy sectors. The ensuing bottom-up equilibrium model with both flexible demand and
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environmental modeling to understand how changing redox conditions (such as hypoxia and re-oxygenation) influence the behavior of actinides like plutonium (Pu) and americium (Am) in sediment and seawater. You
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– Adsorption and reaction of small gaseous non-metal oxides on model mineral particles under light illumination. The position is for four years of doctoral studies, including participation in research and
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, bioinformatics, and ecological modeling. Results will inform future biodiversity monitoring frameworks, adaptive forest management, and conservation policy. At the Department of Wildlife, Fish and Environmental