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performance in heavy industry. You’ll develop and apply state-of-the-art modelling, characterisation, and machine learning techniques to understand how batteries behave and age. Collaborating with project
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and apply state-of-the-art modelling, characterisation, and machine learning techniques to understand how batteries behave and age. Collaborating with project partners, you’ll turn these insights
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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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signal processing schemes using machine learning methods and knowledge of inverse scattering methods (nonlinear Fourier transform). About us: AiPT is one of the world’s leading photonics research centres
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they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI
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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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, ensuring they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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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