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well as familiarity with machine learning workflows, natural language processing (NLP), and text-as-data methods. We are especially interested in applicants who demonstrate a strong substantive interest in using
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natural language processing and machine learning workflows; (3) experimental design and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal
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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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. 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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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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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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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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. 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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background and expertise in one or more of the following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural