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for passionate and highly motivated Teaching Faculty. The Undergraduate Division is seeking teaching faculty to teach an undergraduate course, Machines that Create, an introductory yet comprehensive overview
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methods for predicting the synthesisability of organic molecules Develop and apply informed machine learning methods to chemical problems If appointed at a higher spine point: To assist in the day-to-day
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attention and comprehension in beginning readers. NPJ science of learning, 5(1), 1-10. Givan, P. (2025). Written Ministerial Statement to the Assembly Early Learning and Childcare measures 2025-26. https
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, 16(1), 5396. https://www.nature.com/articles/s41467-025-60943-7 Toutounji, H., Zai, A. T., Tchernichovski, O., Hahnloser*, R. H., & Lipkind*, D. (2024). Learning the sound inventory of a complex vocal
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in academia, industry and many related careers. Visit http://www.sheffield.ac.uk/sgs to learn more. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply
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your communication abilities and experience the breadth of technologies that are used in academia, industry and many related careers. Visit http://www.sheffield.ac.uk/sgs to learn more. Please apply for
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Protection: 8th International Conference, EuroMed 2020, Virtual Event, November 2–5, 2020, Revised Selected Papers Virtual Heritage Learning Environments Pages 427–437. https://doi.org/10.1007/978-3-030-73043
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Accessible Tinnitus Notch Noise Therapy via Machine Learning, Acoustic Metamaterials and Additive Manufacturing (with NHS and TinnitusUK) EPSRC Centre for Doctoral Training in Sustainable Sound
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practical tools deployable in real-world clinical settings. This work is central to a multidisciplinary collaboration bringing together experts in neuroscience, machine learning, and clinical informatics
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD