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challenge meeting this requirement is the simultaneous need for low-power consumption. The main objective of the project is to develop a complete end-to-end high-performance DNN system for on-premise
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project - “Establishment of joint research centre on brain-inspired computing”. He/She will be required to: (a) conduct the research on the development of neuromorphic foundation models and brain
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is
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peer-reviewed journals and/or top-tier conferences. Knowledge & Skills: Strong foundation in machine learning, deep learning, and algorithm development. Proficiency in scientific programming (e.g
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research project/s under the guidance of the grant CIs (Prof Francis, Prof Tanaka, and Dr Hendriksen), and contribute to development of research activities. Support the dissemination of research outcomes
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Responsibilities: Design and implement advanced AI/ML models for healthcare applications, including predictive analytics and generative AI solutions. Develop and validate digital phenotyping algorithms using
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scholarship holder will contribute to several research activities, including: - Design and implementation of event-based data compression algorithms, including lossy and learning-based approaches. - Development
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analysis; (b) develop and implement algorithms for 3D perception (e.g. segmentation, localization and mapping); (c) design and execute experiments to evaluate, validate and refine algorithms and
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Design). Ideal candidates have Specialist Knowledge in Neuromorphic Engineering, with experience in Designing and Building and Implementing FPGA systems, working with and/or developing neuromorphic
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis