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Field
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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employers. About the Global Campuses The university campuses operate as a distributed global network. For example, new programs may be developed and established at one of the network campuses, enhanced
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on developing advanced new algorithms, testing and validation, and applications in medical neuroimaging and non-imaging modalities. The candidate will contribute to the overall research goals and objectives
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AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical imaging QUALIFICATIONS Successful applicants will have: a PhD in
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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and financial planning tools; this includes modeling new algorithms, creating functional specifications, and testing and/or validating new financial planning tools. Collaborate with other members
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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, the post-doctoral fellow will consider designing distributed learning algorithms for streaming manifold-valued data. Experiments will be carried out on urban, coastal, and underwater DAS data. The novelty
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frameworks, as they impose minimal, if any, assumptions about the underlying data distribution, making them more effective for detecting a wide range of changes. The CPD algorithms will be designed
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security algorithms to be implemented in the next generation of constellation satellites; collaboration with the RF payload colleagues in analysing and profiling the implementation of these algorithms