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Field
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of this PhD is to use optical flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and
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assist irrigation management and promote improved representation of irrigation processes in weather and climate models. Satellite data will be used to obtain a more accurate temporal mapping of irrigation
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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used to train surrogate models that can instantly predict quantities required by component scale CFD wall boiling models for different flow conditions and heat transfer surfaces. Key milestones
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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freshwater fishes, structured around the following objectives: Use the LOC to map the freshwater fish distributions in Madagascar, including threatened, invasive and human food species Create predictive models
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prognostic models for filter degradation. Integrated Drive Generator (IDG) Rig: Simulates the operation of an aircraft's IDG, used to investigate fault detection, diagnostics, and prognostics in power
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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combines microbial genomics, transcriptomics, and in vitro infection models to explore the adaptive trade-offs between drug resistance and virulence phenotypes. The position is funded for 3 years and
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and heat transfer in geothermal systems under high-pressure and high-temperature conditions relevant to AGS. • Developing high-fidelity direct numerical simulation (DNS) models to map