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geolocated social media data, and computational techniques from network science and machine learning. It is interdisciplinary, combining theories of healthy and accessible cities with computational data
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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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this industrial PhD studentship in Physics – fully funded by the University of Exeter and Leonardo UK. We’re looking for a student who has a passion for science, with ambition to learn and apply their own ideas
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algorithms that combine Reinforcement Learning techniques like Partially Observable Markov Decision Processes (POMDPs) with cognitive inference modules capable of modelling human beliefs, intentions, and goals
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power, for example feminist, intersectional, socio-legal, or related frameworks; confidence, or willingness to learn, working with structured datasets as part of mixed-methods research; ability integrate
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jointly learn from images and text, most current systems are still limited in three important ways: they primarily rely on statistical pattern recognition rather than structured clinical reasoning
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are proud signatories of the Armed Forces Covenant and welcome applications from service people. Benefits We offer some fantastic benefits including: 41 days leave per year options for flexible working
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flexible, supportive and inclusive team environment at a research-intensive university, where your work is seen and has meaning. Personally tailored training opportunities and the chance to learn and utilise
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The University of Exeter's St Luke’s Swim School are looking for passionate, enthusiastic and organised swimming teachers to join our Swim England Learn to Swim programme, delivered at our indoor