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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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(7T fMRI, MR Spectroscopy), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics
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background in mathematics, statistics, population genetics, phylogenetics, epidemiological modelling, or machine learning. Highly motivated candidates with some, but not all, of the skills requested will be
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to conduct multidisciplinary research around robot learning for autonomous robotic chemists, with a background of excellent research outputs across Robotics and Machine Learning, ideally with a background in
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to conduct multidisciplinary research around robot learning for autonomous robotic chemists, with a background of excellent research outputs across Robotics and Machine Learning, ideally with a background in
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research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub
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to develop a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. The Team is looking to appoint one Postdoctoral Research Associate on Machine-Learning Assisted