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the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree from a recognized institution (no more than 5 years since completing the doctoral degree) Doctoral research in the area of machine
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processes for the recovery of minerals from desalination reject brine. The role will involve development of a range of mineral extraction processes and the lab and pilot scale. This will include development
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
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blind and low-vision individuals in navigating both outdoor and indoor urban spaces. The project's initial phase will employ machine learning models, computer vision algorithms, and real-time sensory
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engineering, computer engineering, computer science or a related field by the time they join, and at least three years of post-doctorate experience. Excellent communication skills in English, the ability
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or other related department to apply. The successful applicants will design controllers for a variety of
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decision process for sustainable transport modes and transport innovations. Research is interdisciplinary involving behavioral economics, psychology, neuroscience, computer science applied to the transport
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multimodal interaction are encouraged to apply. Applicants must have received a Ph.D. in electrical engineering, computer engineering, computer science or a related field by the time they join, and at least
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, and Full Professor) to apply, in areas including, but not limited to the following: Computer systems Databases Theoretical computer science Security Programming languages and compilers Software