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Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can contribute to the excellence of our academic community. The Sonenblum Clinical Research Group in the...
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets Experience in statistical or scientific programming (ideally R and/or
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation
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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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developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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Sciences and Mathematics The college is home to five academic departments: Biological Sciences, Chemistry and Biochemistry, Geography and the Environment, Mathematics, and Physics and Astronomy. The college
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Applications are invited for a Research and Innovation Associate in the atomic astrophysics group, Department of Applied Mathematics and Theoretical Physics, University of Cambridge. The successful
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About us The Social Computation and Representation Lab (SoCR Lab; www.socrlab.net) uses mathematical models and causal experimental designs to understand the fundamental rules behind human and AI