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parameters by trial-and-error, leading to a time consuming sub-optimal selection. In the domain of high precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities
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variable load and transient conditions. Develop a transient model to assess behavior during power demand fluctuations and optimize operational strategies. Study the degradation mechanisms of the HT-PEMFC
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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limited. We are offering a PhD scholarship for a student to develop ambitious new machine learning strategies for generating AI-ready data. You will work at the frontier of active learning and ML-guided
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to capture vPvM chemicals in water. Optimize effect-directed analysis and implement suitable in vitro assays Investigate operational waterworks and if possible test pilot-scale systems such as advanced
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parameters by trial-and-error, leading to a time consuming sub-optimal selection. In the domain of high precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities
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objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your