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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current
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be a game changer. Deep learning models can learn the mapping between material states and ultrasonic responses from simulation data, delivering quantitative predictions once trained, and remarkably
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benchmark chemometric and physics-informed machine learning models to monitor, forecast, and ultimately control critical process parameters, implanting these models in advanced control frameworks to optimize
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. This project proposes the development of a new CFD simulator for offshore renewable energy applications based on physics-informed deep learning that offers greater efficiency and robustness. This is a unique and
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analysis equipment and software and learn how ideas emerging from academic research can be developed towards commercial application. You will also undertake a secondment at the University of Liverpool’s
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advanced machine learning techniques Optical design and miniaturization of a novel spectroscopic sensor based on freeform optics, optimized for agrifood applications For this function, our Brussels
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for education and research. Learn more about our codes of conduct We are located on one physical campus, in the heart of Amsterdam's Zuidas business district, with excellent location and accessibility. Over 6,150
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this pathogen to cause infections, survive attacks by innate immune cells (macrophages and neutrophils), and develop resistance to antifungal agents (see selected publications below). The PhD student will learn
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, relating to craniofacial identification research and machine learning. You will require a computer science background. You will be applying AI and/or machine learning to Face Lab processes in relation
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(preferably in Python, including deep learning frameworks such as PyTorch); affinity with medical image analysis and computational modeling; experience with neural networks for image analysis, generative