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interactions between these levels as well. In order to capture the structure and complexity of relationships between the nodes of networks with a mul-tidimensional nature, tensors are used to represent
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and coordinate with customers and vendors. Ability to perform network troubleshooting, diagnostics, and failure analysis for complex network and connectivity issues. Required Qualifications Bachelor’s
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, where current workflows still depend on substantial manual model clean-up. By removing the reliance on de-featuring and enabling reliable high-order meshing of complex shapes, the project will
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installation, repair, configuration, maintenance, and management of workstations, portable computing devices, audiovisual systems, network connections, and associated peripheral equipment. The position performs
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installation, repair, configuration, maintenance, and management of workstations, portable computing devices, audiovisual systems, network connections, and associated peripheral equipment. The position performs
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University of California, San Francisco | San Francisco, California | United States | 28 minutes ago
initiatives. You'll be part of a dynamic Financial Services Team where collaboration and mentorship are at the heart of everything we do. Whether you're working on complex financial analysis, budget management
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 7 hours ago
of EMS systems. Direct-field experience with local, state and federal EMS programs. Progressively graded medical control responsibilities for complex EMS systems with acquired proficiencies in fire-based
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Posting Description IT SUPPORT SPECIALIST, Information Systems and Technology (IS&T), in the Escalations team identifies emerging and complex IT issues and problems, and facilitates the resolution
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only