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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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development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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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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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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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 emergence of edge computing, data storage will become more geo-distributed to account for performance or regulatory constraints. One challenge is to maintain an up-to-date view of available content in such a