361 machine-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions
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Field
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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integrating power electronic converters and electrical machines we can use common structures and systems to greatly reduce, material usage and energy consumption. Through a multidisciplinary research approach
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also include generative or predictive modeling of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access
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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and
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. The role We are looking for a Senior Power Electronics Researcher to support our e-Auto Challenge Program hosted by the Automotive and Surface Transportation (AST) Research Centre. The successful candidate
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of Electronic and Computer Engineering, University of Limerick., • Prof Colin Fitzpatrick, Department of Electronic and Computer Engineering, University of Limerick. Overview: The ECODESIGN Doctoral Network (DN
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microscopy and SEM, with computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties
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automotive and aerospace electrification. Applications for this PhD position are invited at the Power Electronics and Machines Centre, University of Nottingham. Based in a recently built £18M facility
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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expertise in artificial intelligence, computer vision, human-computer interaction, and psychology. Its technical core lies in developing robust and adaptive visual speech recognition models. Close