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networking testing equipment to diagnose computer hardware and troubleshoot network issues. Utilize Intune, Entra, MECM, Active Directory, DHCP, and Vulnerability Management tools to support the engineering
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algorithm-hardware co-design to enable efficient and accurate deployment of AI algorithms on robotic, edge, and heterogeneous computing platforms. Develop methods for efficient deployment of AI models
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disciplines such as neuroscience/cognitive science, AI and machine learning, robotics, engineering, computer vision, and signal processing. Details of this year’s workshop are at https://sites.google.com/view
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direct customer support and training contact as well as a higher level resource for undergraduate student technicians to assist users with Artificial Intelligence (AI) projects, robotics, edge computing
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complexity to higher education system employees. This position assists users in successfully utilizing their hardware and software workstations including troubleshooting operating systems, desktop applications
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Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more information. About UT Dallas The University of Texas at Dallas is committed to graduating well-rounded members
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Framework Programme? Not funded by a EU programme Reference Number 173095 Is the Job related to staff position within a Research Infrastructure? No Offer Description CASTRO aims to develop wireless signal
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on-call rotation may be required Travel to locations on and off campus and move throughout various buildings to provide support and deliver/retrieve computer hardware and parts is required The ability
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processor-level firmware development, real-time data handling, and mechanical integration of new sensors and hardware components. The person in this role will be involved in the full development cycle—from
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well as large-scale GPU computing facilities for deep learning. We are looking for a Senior Research Engineer to manage the EEE GPU Cluster. The role will focus on leading the EEE GPU Cluster team and in charge