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that integrates satellite-derived embeddings with hydrodynamic simulations for real-time flood prediction anywhere in the UK. Research questions focus on learning shared representations, replacing expensive
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source within a defined quality level. Only if this is done can the behavior of the devices be explained and predicted in a deterministic manner. In this PhD position, you will analyze the above task on an
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industry, papermaking, or oil extraction. It is essential to be able to predict the flow regimes inside the receiver for two main reasons. First, steam production directly depends on the prevailing flow
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D'Souza ([email protected] ). Please read the description below in full before directly contacting us by email. Your role and goals You will develop data-driven and machine learning workflows to predict
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together with other energy assets, such as electrical boilers, within a Model Predictive Control (MPC) framework that optimally balances electricity and heat production. Within FLEX-SMR, this PhD focuses
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
phenomena. New meta-model architectures based on learning may be proposed and tested on complex EDF use cases. However, this is not sufficient: can such a surrogate, learned from simulation data, predict
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16th August 2026 Languages English English English The Department of Civil and Environmental Engineering has a vacancy for a PhD in Predictive AI-Based Maintenance and Optimization of Building
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develop data-driven and machine learning workflows to predict Wannier Hamiltonians, phonon properties, and electron–phonon coupling in layered transition-metal dichalcogenides (TMDCs) such as MoS₂, WS
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products. At NTNU, a central part of the project is the development of more predictable and efficient methods for the refactoring and heterologous expression of biosynthetic gene clusters (BGCs). The PhD
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be developed, capable of operating in reactive, online settings where the data distribution may shift over time. Key challenges include detecting prediction failures, designing self-correcting update