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Research Studentship in Numerical Optimisation and Control 3.5-year D.Phil. studentship Project: Embedded Optimisation for Autonomous Spacecraft Control Supervisors: Prof Paul Goulart The project
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sector. How do we protect fundamental rights when algorithms help decide on who receives public benefits, how to perform enforcement or how to enact environmental policy? What is the role of the state, and
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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of nanofabricated sample supports and tracking algorithms for 5D electron diffraction (5DED). EMAT is one of the leading electron microscopy centers in the world and has a vast expertise in both fundamental and
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abort (or not engage) if the bright white lines that fit a defined and rigid expectation are not clearly visible. These systems use algorithms, rather than AI machine learning, to detect road markings and
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convection while also capturing the large-scale global circulation. Further into the project, there is the possibility to work with moisture or cloud tracking algorithms, regional models, and validation with
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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to the full development pipeline: from algorithm design and implementation to clinical integration and evaluation. You will also work on improving prognostic models using (neuro-symbolic) AI and develop
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networks, making use of intelligent AI-driven control planes. The work will involve: i) (i) development of network probing algorithms for OSNR/GSNR measurement automation; (ii) development of adaptive ML and
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Primary supervisor - Prof Kate Kemsley Join us to research and develop advanced analytical methods for tackling food fraud head-on! Economically motivated adulteration of foods is a significant