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strong plus. • Excellent software architecture design capabilities and experience with cloud/edge computing deployment. • Strong written and spoken communication skills. • Open to fixed-term
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of Singapore (NUS). The selected candidate is expected to: • contribute to AI and software stack integration from architecture to vision task 1. Dataset, pre-trained model gathering, software sandbox and
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 9 hours ago
Position Information General Information Position Number POST40 Working Title Postdoc Research Fellow; School of Architecture Division Academic Affairs Department Col of Arts & Architecture (Col
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non-deterministic behaviour, data-driven failure modes, human-machine interaction and emergent system effects; proposing and assessing architectural patterns for the safe integration of AI functions
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delivering the research programme, contributing to the project's technical architecture, software development, dissemination of findings and overall research impact. The postholder will work collaboratively
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: FastTrackAI: Fast-Tracking AI for Scientific Discovery with Accelerated Networking and Computation on Modern Architectures in Singapore Project Introduction: The advancement of accelerated computation and
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on hardware and software co-design for systems targeting energy-efficient chips. The role involves developing, evaluating, and optimizing system-level techniques across hardware architecture, software stack
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the field of architecture or related fields; Proficiency in computer-aided design, graphics and video software, as well as data processing and word processing software, amongst others; Advanced knowledge
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methods and deep learning to enable scientific reasoning. Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures
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. The Ule Lab is highly collaborative. You will join a multidisciplinary team on the Denmark Hill Campus with a leading role in: Developing scalable analysis pipelines and software architecture for handling