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Summary Positioned within Ulster University’s AI Research Centre (AIRC) in the School of Computing, this research theme focuses on advancing artificial intelligence for environmental sustainability
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record in astrocyte-neuron interaction modelling, published in Frontiers in Computational Neuroscience, PLoS Computational Biology, Neurocomputing, and IEEE Transactions on Neural Systems and
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Summary This PhD project will develop and validate an ultrasound-based system for real-time monitoring of bone temperature and insertion forces during orthopaedic implant procedures. Excessive heat
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energy. A good understanding of the physics of air flow and heat transfer is required for this project. An understanding of thermal comfort is desirable. The work will involve experimental analysis using
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, and high-field NMR, using Ulster’s state-of-the-art facilities and Northern Ireland’s High-Performance Computing (NI-HPC) resources. You will gain skills in: Generative AI for structure prediction
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the country’s net zero solutions and deliver substantial economic benefits. Recent advances in geothermal energy include integrating closed-loop ground source heat pump systems into civil engineering
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Computational Biology communities. The PhD researcher will gain training in: AI and ML Computational modelling of behaviour and brain function High-performance computing Applied mathematics and statistics
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, mitigates the impact of climate variability, and enables year-round production of high-quality crops. However, the energy-intensive nature of vertical farming, particularly its reliance on artificial lighting
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. et al. (2024). Design of high-performance entangling logic in silicon quantum dot systems with Bayesian optimization. Scientific Reports 14, 10080. https://doi.org/10.1038/s41598-024-60478-9
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Summary Robotic welding is used for joining large, high-value metal components. Yet, when quality drifts go unnoticed with bead misalignment, arc instability, or defects, the manufacturers face