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project, “Material Model Discovery from Physics-Encoded Neural Networks”, aims to discover material models that give unprecedented accuracy and computational efficiency, enabling engineers to fully exploit
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. The neural networks currently being developed at LISTIC to detect and segment areas of movement in interferograms will be tested and validated at known sites so that these methods can then be generalized
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STFC - The Science and Technology Facilities Council; | Harwell, England | United Kingdom | 20 days ago
, for further details at: https://www.gov.uk/government/organisations/united-kingdom-security-vetting Join us and discover what’s possible! To apply for this role, please click on the 'Apply' button above.
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, hardware and software installation, troubleshooting, repair and maintenance, Faculty and Staff consultation and training, and Network troubleshooting and maintenance of the department's web server and for
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Rutgers' computing environment. The position will work with senior security staff on cybersecurity operations within Enterprise Infrastructure to discover and remediate security threats on networks
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statement of research interests, and three letters of reference, should be submitted through the application portal located at: https://indiana.peopleadmin.com/postings/31658 Review of applications will begin
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to augment classical spike train analysis methods particularly those developed by Prof. Grün and others for detecting synchronous spiking activity with AI-based enhancements. After profiling the classical
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control, CCTV, intrusion detection, communication, cable management, electronic locks, Wi-Fi locks, network switches, point sensors, signaling devices and associated hardware. Responds to situations where
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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the Job related to staff position within a Research Infrastructure? No Offer Description About the network StraDiVarious (Strains, Diagnostics and Variants) (www.stradivarious.eu ) is a European-wide