421 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions in United Kingdom
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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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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models
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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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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