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physical computing systems design. Our infrastructure supports disciplines ranging from engineering and physics to life sciences, climate modelling, machine learning and computer vision, and wider data
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. MakingAI confronts the challenge of synthesizing these hybrid 'messy' data, by integrating artificial intelligence, particularly multimodal learning and machine reasoning, with Technical Art History
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methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and academia. The candidate
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Interaction and physical computing. Supervise postgraduate research students working on topics related to hardware, fabrication and/or interactive systems. Teach effectively across the full curriculum
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We are seeking a Research Associate with expertise in machine learning and causal inference to join the University of Manchester spoke of “CHAI hub: Causality in Healthcare and AI”. The CHAI hub
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Computer Engineering, Computer Science, Computational Science-based discipline or equivalent experience The preferred candidates will be flexible and independent to learn new languages and find the right
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to life sciences, climate modelling, machine learning and computer vision, and wider data-driven research. Colleagues in the newly established Bristol Centre for Supercomputing (BriCS) operate the recent
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in the field, including the application to artificial intelligence and machine learning. We consider computer science challenges from a broad perspective. Members of the department regularly publish in
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., Ntoa, S., Salvendy, G. (eds) HCI International 2023 Posters. HCII 2023. Communications in Computer and Information Science, vol 1833. Springer, Cham. https://doi.org/10.1007/978-3-031-35992-7_2 Familoni
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and machine learning techniques for the design of superconducting qubits, one of the leading qubit modalities used in today’s quantum computers. The optimal design of superconducting qubits is a highly