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EngD: Enhancing productivity in manufacturing through automation and autonomy in computer aided process planning (sponsored by Boeing) EPSRC Centre for Doctoral Training in Machining, Assembly, and
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artificial intelligence/machine learning may be applied are encouraged to apply. If you are interested in research in brain-machine interfaces, and are unsure about whether you have the right background
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be found on our website https://www.ucl.ac.uk/biosciences This is an exciting opportunity to join the Cox Lab in the UCL Centre for Integrative Anatomy. The successful applicant will conduct research
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to demonstrate their right to work in the UK prior to commencing employment and obtain the right to work in the UK. Information on other visa options is available at https://www.gov.uk/check-uk-visa . To apply
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Pol II on genes e.g. https://doi.org/10.64898/2025.12.04.692291 ; https://doi.org/10.1016/j.molcel.2024.11.024 . The goal of this project is to understand the molecular mechanisms by which several newly
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manufacturing sectors. Applicants should have a good background in mechanical, energy, or related engineering disciplines, with knowledge of thermal-fluid sciences, and be familiar with or willing to learn
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analysis (Excel, R, Python, Prism etc). D4 Knowledge of applying artificial intelligence and/or machine learning approaches to biological image analysis or data interpretation. Experience Essential E1
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that developments are well understood and embedded. To apply electrical/electronic design skills to create a prototype including circuit analysis, computer aided design and complex simulation tools, e.g. MATLAB/SPICE
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-based transfer learning classification model for two-class motor imagery brain-computer interface. International Journal of Neural Systems (IJNS). https://doi.org/10.1142/S0129065719500254 * Kudithipudi
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will also be considered. References Korsós et al., ApJL 802 L21 (2015) https://iopscience.iop.org/article/10.1088/2041-8205/802/2/L21 Korsós, Chatterjee, Erdélyi, ApJ 857 103 (2018) https