554 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" positions at University of Sheffield
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“An improved machining temperature prediction model for aerospace alloys: Effect of cutting edge radius and tool wear”, Journal of Manufacturing Processes 133 (2025) 1100–1110. https://doi.org/10.1016/j.jmapro
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with the CDT’s aim to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be
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the third Higgs boson decays to two tau leptons, or another highly sensitive combination. The student will gain expertise in machine learning techniques for signal-background discrimination and will
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acids institute (https://sheffield.ac.uk/nucleic-acids) and the centre for Single Molecule biology (https://smash.sites.sheffield.ac.uk/), providing additional expertise. This project will contribute
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neurological and cardiovascular disorders. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying References GONZÁLEZ-SANTANA, A., ESTÉVEZ-HERRERA, J., SEWARD
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to apply can be found at the following link: https://www.sheffield.ac.uk/acse/research-degrees/applyphd Applicants can apply for a Scholarship from the University of Sheffield but should note that
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. This PhD project will build directly on this work by using ideas from machine learning—originally developed to study the movement of larger organisms—to understand how bacteria process information in
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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data
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, November, 427–435. https://doi.org/10.1201/9781003558859-47 [2] Rui, S., Xu, H., Teng, L., Xi, C., Sun, X., Zhang, H., & Shen, K. (2023). A Framework for Mooring and Anchor Design in Sand Considering Seabed
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Ability to lead and work in teams Essential Application/Interview Experience and capability in blast computational simulations using codes such as Viper:: Blast, machine learning, and/or LS Dyna Desirable