206 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" Fellowship positions in United Kingdom
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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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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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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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-centric machine-learning frameworks for large-scale sequence-structure analysis and functional prediction. The role involves designing, implementing, and benchmarking computational models; developing and
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machine learning, spatial audio & 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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your machine learning expertise to cutting-edge automated optimisation challenges? We are seeking a Research Fellow in Digital Chemistry and Engineering to combine self-optimising flow reactor technology
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should also have an interest in data science, machine learning tools or artificial intelligence as applied to biological systems related to immune therapy of cancer. The postholder should be committed
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machine learning with rigorous statistical methods to address fundamental questions in cosmology and beyond. The research aims are to develop novel inference frameworks for cosmology and apply them
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Are you interested in developing interpretable AI models for the next generation of green syntheses? Do you have experience in AI/Machine Learning, or computational modelling of organic reactions
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deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in human factors with applications