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Field
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research in the field of AI for healthcare autonomous systems. Activities on non-healthcare systems could occasionally be requested. • Undertake research from algorithm development to real time
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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative
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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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, AI, and other algorithmic techniques in qualitative social scientific research. In line with the interdisciplinary and reflexive ethos of DIVSOL, attention to the societal implications of AI is an
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performance. The developed methods and algorithms will be validated on both scaled in-house test setups and Å Energi’s pilot HEPs, in collaboration with Volue Industrial IoT AS. Active collaboration with other
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and Machine Learning tools and algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability
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algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively with
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data to assess fault impacts on efficiency and to forecast system performance. The developed methods and algorithms will be validated on both scaled in-house test setups and Å Energi’s pilot HEPs, in
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dataset from various internal and external resources. ● Understand and apply best-in-class algorithms to address biological and clinical questions. ● Collaborate effectively within an interdisciplinary team
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., NumPy, OpenCV, scikit-learn). Experience implementing and evaluating state-of-the-art tracking algorithms such as DeepSORT, ByteTrack, and Transformer-based approaches. Proven ability to design and run