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Field
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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and its implementation in distributed systems. Main responsibilities: Research, develop, and optimise machine learning algorithms, including deep learning, for AV control and coordination. Apply multi
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theoretical physics, whose responsibilities relate to distributed systems and the GPU optimization of AI algorithms. We expect the team to grow in size considerably over the next few years, and are looking
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Data Research Network Canada (HDRN Canada), a research-enabling, distributed network that supports multi-regional, person-focused research. The work of HDRN Canada is supported by a seven-year, $39M
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the effectiveness of different courses of action using predictive algorithms. They assess the effectiveness and accuracy of new data sources and data gathering techniques. Data Scientist is an expert in
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Faculty.Professor.Assistant - Full-Time SCI-Office of the Dean - Pennsylvania-Pittsburgh - (24008558) Tenure-Stream Assistant Professor for Quantum Algorithms As the University of Pittsburgh’s
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. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms
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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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heterogeneity, i.e., the fact that clients' local datasets are in general drawn from different distributions. Statistical heterogeneity for example slows down the convergence of FL algorithms [5]. In this thesis
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machine learning techniques, predictive algorithms, and AI-powered tools to extract actionable insights to drive US Commercial strategies and tactics. Manage and mentor a team of data scientists (internal