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physics. Development of new artificial-intelligence and machine-learning techniques for high-energy and nuclear physics. Close interaction with our collaborators in the EIC and the BNL theory group will be
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. Research opportunities will focus on the use of novel modeling tools for hydrology and water resources systems, with an emphasis on machine learning and remote sensing, with a focus on developing detailed
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal
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sufficiently versatile to rapidly acquire the required capacity. You will have : A PhD in gut microbiology or closely related field Good knowledge of gut modelling and general microbiology Experience in
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Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of machine learning and deep neural networks Free Probability aspects of Quantum
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Scholar appointments to a total of five years, including postdoctoral experience(s) at other institutions. The University of Washington and the International Union, Automobile, Aerospace and Agricultural
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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Required qualifications: PhD in evolutionary ecology or related fields Strong track record of publishing scientific research Familiarity with urban evolutionary biology and wildlife biology. Strong ability