430 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions in United Kingdom
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analysing qualitative data, synthesising findings, and supporting the preparation of reports, presentations, and academic publications. This role will be based at the Centre for Appearance Research (CAR
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delivering high-quality teaching and learning, and research and innovation with a campus-wide focus on providing a sector-leading student experience. A culturally rich university with a palpable commitment to
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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication skills
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Machine Learning (OxCSML) research group, with responsibility for leading and carrying out research pertinent to the project, as well as day-to-day management of research activities relevant to the project
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information/data from one structure can be used to manage similar structures from the same population. New machine learning, sensing and digital twin technologies will be developed with the aim of driving new
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, software engineering, Embedded Systems, Artificial Intelligence / Machine Learning, data science, or closely related disciplines or significant practical/industrial experience. Significant postdoctoral
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, computer vision, and predictive modelling, alongside excellent IT, analytical, interpersonal and communication skills in spoken and written English. You must be able to collect, process and present data with
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responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and execute methods for characterizing and linking the texture and
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch