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on cutting-edge topics such as: Data-efficient learning Explainable AI Memory-efficient deep learning Energy-efficient deep learning Parameter-efficient fine-tuning of foundational models The PhD studentship
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expands—driven by technological progress, regulatory alignment, and increasing demand, with an estimated market value of ~$719 billion by 2029—persistent issues like soft tissue erosion and inflammatory
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, several parameters and estimates may be ambiguous, i.e., imprecise, or unknown. Particularly, experimental research has shown that people are averse to such ambiguity, and theoretical researchers have
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carrying partially unknown loads. This uncertainty results in conservative estimates of braking rates and dynamic performance, reducing efficiency both at the individual train level and across the network
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). Knowledge of/experience in Bayesian networks is appreciated. Knowledge of/experience in AutoML or hyper-parameter optimisation is also appreciated. We offer We will give you a temporary employment contract
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gas turbine sensor data, if available, will be utilized to validate the developed digital twin in order to estimate non-measurable health parameters of major gas path components, including compressors
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operation and track its health, recurrent neural networks, particle and/or extended Kalman filters, and inverse parameter estimation methods might be worth exploring. By uncovering the dependency between
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and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good communication skills are also essential. This award is open to
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track its health, recurrent neural networks, particle and/or extended Kalman filters, and inverse parameter estimation methods might be worth exploring. By uncovering the dependency between the cell
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stability/lifetime of perovskite solar cells strongly depends on many—largely unknown—parameters. This is a problem in any research lab, but even more so at the industrial scale. This project will tackle