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Field
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project will involve optimizing the trapping conditions—such as laser power, wavelength, and nanostructure geometry—to prevent photodamage while achieving strong signal enhancement. The project will also
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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algorithms for data processing, assisted or automated flaw detection, 3D EM solvers, and synthetic aperture radar (SAR) focusing will be used to refine spatial resolution. Applicants should have, or expect
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When light illuminates nano-sized metallic structures, the free electrons in the metal collectively oscillate, creating `plasmons'. By specifically designing the geometry and arrangement of the nano
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When light illuminates nano-sized metallic structures, the free electrons in the metal collectively oscillate, creating `plasmons'. By specifically designing the geometry and arrangement of the nano
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap