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acquire the right part of a specific course in a cost-efficient way. The aim of the project is to design new analytical and simulation models and solution approaches to support strategic and real-time
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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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contribute to smart grids that make energy networks more efficient, mathematical models that assist medical doctors, schedules that make hospitals more efficient and numerical schemes to study multiscale fluid
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contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics
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productivity and community biomass to size spectra under stress. Examples of the approach can be found in Ecological Modelling 205: 196-208 and Ecological Indicators 79: 114-121. You will be part of the WP3 team
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
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/GNC systems has traditionally relied on model-based techniques, which in turn, have their foundations in a solid body of mathematical proofs (such as guarantees of stability and robustness
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Organisation Job description A postdoc position in computational social choice for AI Safety is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence
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Organisation Job description A postdoc position in computational social choice for AI Safety is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence
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propulsion, engine clustering, low structural ratio and low-cost system-integrated avionics; develop mathematical models relating to the cryogenic liquid engines and their components to be applied