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Field
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expertise ranging from mathematical modelling to chemistry, molecular and cell biology, material sciences and engineering, and medical devices. The Research Fellow will be working in collaboration with
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co-develop a next-generation ocean component for integration into the universal climate model OASIS. We are looking for a candidate with a PhD (or equivalent) in Physical Oceanography, Atmospheric
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English English PhD Research Fellow in Machine Learning and Distributed Data Processing Apply for this job See advertisement Job description Position as PhD Research Fellow in Machine Learning and
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a postdoctoral candidate in the area of federated learning and wireless communications. The candidate must hold (or about to complete) a PhD in the related fields. The candidate will be involved in a
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PhD, or near to completion (or equivalent experience) in a relevant field, including statistics, mathematics, computer science, epidemiology Strong mathematical and quantitative skills Familiarity
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model reliability and predictive confidence Publish high-quality scientific results in Tier-1 journals Job Requirements: A PhD degree in Mathematics, Computer Sciences, or related areas, with focus
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conferences. Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline. Person Specification PhD (or near to completion or equivalent experience) in a
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regimes of deep networks. Basic Qualifications: A PhD is required. We seek candidates with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics
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and mathematics with a good grounding in geophysics, remote sensing and data analysis. Candidates must have a Master’s degree in geophysics, mathematics signal processing or physics, and a PhD in
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and mathematics with a good grounding in geophysics, remote sensing and data analysis. Candidates must have a Master’s degree in geophysics, mathematics signal processing or physics, and a PhD in