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to exposure misclassification. This is particularly true for social housing residents, who are more likely to live in poor-quality housing and hence be more vulnerable to climate change. The primary
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and implementing an embedded optimisation algorithm on representative hardware platforms to demonstrate feasibility and real-time performance. The primary application will be autonomous 6-DoF Moon
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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clear aptitude for research. You will have a Masters in a relevant discipline and will definitely have a 1st or 2:1 Bachelors degree (or equivalent). You will be able to demonstrate excellent mathematical
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degree, for example, Doctor of Philosophy or Master of Philosophy, for which a tuition fee waiver will be granted. As a requirement of the tuition fee waiver, the post-holder may also be required to tutor
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extension to a total maximum of 4 years is possible. Your future tasks: You actively participate in research, teaching & administration, which means: Your main task is to complete and to submit your
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studentship include? This is a fully funded PhD studentship which includes fees and stipend. Eligibility criteria Entry requirements: A Bachelor of Science degree in 2:1 or above and/or master's degree in
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Primary supervisor - Prof Katharine Hendry (British Antarctic Survey & UEA Honorary Professor) Secondary supervisor - Prof Dorothee Bakker Fragile polar ecosystems are critical to the global
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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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are encouraged (laura.winchester@psych.ox.ac.uk ). You will need to apply for this studentship via the main University online graduate application form, and pay an application fee of £20. The application form, all