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fully funded, three-year PhD studentship starting in October 2025, focused on one of the following research objectives: To develop biomimetic designs that enhance energy harvesting and bioelectronic
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learning. The project involves a collaborative team, including a postdoctoral researcher and a PhD student, with specific objectives: Define and acquire a comprehensive database of high-quality video priors
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backgrounds who are eager to contribute to cutting-edge research at the forefront of nuclear technology. The PhD studentship comes with a competitive stipend. Objectives This PhD opportunity, offered in
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lower orbit space debris). The increasing density of space objects in Lower Earth Orbit (LEO), including the proliferation of satellite constellations, further exacerbates the risk of collisions and the
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through advanced modelling and simulation. A key objective is to validate and optimize poroelastic finite element models of brain tissue, making them more accurate and clinically relevant. Additionally
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in a more accurate analysis of optimizing the service performance. Computer vision approaches such as ones for object identification and action recognition can help to automatically identify deviations
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and trends in wall adhesion. Through Syngenta’s involvement, we will have access to experimental to guide the project inform modelling decisions. Project Objectives for the PhD project The aim
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of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
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analysis of experimental data, material characterization and writing skills. Primary objectives: Train the student with photocatalytic experimental skills. Teach the student how to synthesise photocatalysts
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are expected to include: •Robust and “functionally explainable” machine-aided decision support for Safety and Mission Critical objectives e.g. fault detection/tracing, evasive manoeuvring, target selection etc