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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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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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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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knowledge in building ventilation systems, heat transfer, fluid dynamics, machine learning, data analysis, and coding e.g., Python. Understand sensors, actuators, data acquisition, and control systems
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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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of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us