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environmental science is of supreme importance. Students entering the science classroom bring well-developed intuitive frameworks that help them understand, explain, and predict the world around them. These
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to pre-train a common GNN backbone model capable of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a
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trends and composition analysis, refractive index determination, and morphology for applications such as environmental monitoring, nuclear non-proliferation, and improving predictive modeling tools (e.g
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profiling, and gnotobiotic mouse models to create predictions for which infants are most susceptible to sepsis. We are looking for an enthusiastic Postdoctoral Research Associate to join our team
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predicting pollutant dispersion in complex environments like industrial sites remains difficult due to fluctuating wind conditions and obstacles. This PhD project offers a unique opportunity to develop
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at two levels: SAACD Component: This is a UAV made up of hardware and software sub-systems, capable of observing, predicting, deciding and reconfiguring itself to fulfil its mission (e.g. surveillance
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rate and provide a stipend of no less than the standard UK Research Council rate (currently set at £20,780 p.a.) for 4 years. Please note the eligibility criteria set out by the UKRI at: https
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-related challenges in maritime transportation systems; 2) supporting the development and application of quantitative and data-driven models for assessing and predicting risks and system performance; and 3
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the University of Porto (FEUP), under the scientific supervision of Professor Ana Rosanete Lourenço Reis. Grant duration: Initial duration of 6 months, with the predicted starting date in April 2026
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Systems Engineering (Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support Platforms) as part of the CTECH Postdoctoral Fellows program. This