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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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movement; (iii) generate benefits for both society and the environment by guiding possible mitigation strategies; and (iv) drive technological progress through the development of novel algorithms
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and/or pump-probe techniques. Strong optics experience including building and/or adapting setups is essential, and experience working with coding, automation and algorithm development highly desired
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and
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currently leading the NeuroHand project—a UKRI-funded programme focused on the development of a soft robotic exoskeleton glove for stroke rehabilitation. The role provides an exciting opportunity
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, workforce development and leadership, policy, and advocacy. Background City, University of London along with Otto von Guericke University Magdeburg, Lund University, National Technical University of Athens
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currently leading the NeuroHand project—a UKRI-funded programme focused on the development of a soft robotic exoskeleton glove for stroke rehabilitation. The role provides an exciting opportunity
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algorithms, ideally in the healthcare or mental health domain Desirable criteria Track record of successful research grant applications, or attempts to obtain grant funding. Previous development of ML-based