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, interdisciplinary research group, including a postdoc, DTP students, and technicians. Training will include fieldwork, bird handling, ringing, lab techniques in molecular biology, microbiome sequencing
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
distributed infrastructure Applications of agentic AI What You Will Get An inclusive and open-minded research environment that bridges theoretical thinking and system building, with opportunities to publish and
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framework to accommodate new components like EV chargers and distributed generation, and you will apply these insights to both large-signal and small-signal stability analyses. Working closely with academic
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new brain stimulation methods, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and psychiatric disorders. Number of awards
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like EV chargers and distributed generation, and you will apply these insights to both large-signal and small-signal stability analyses. Working closely with academic and industrial partners, you will
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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can feed directly into precision surgery algorithms and clinical trials. Few PhD projects offer such a clear line of sight from variant to mechanism to clinical translation. Located on the thriving
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, particularly in computer networks, operating systems, computer architecture and distributed systems Excellent programming, system building and measurement skills are required Be familiar with, and ideally worked
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distribution and with synthesised future sea-ice distributions; examine the impacts on barrier wind structure and associated surface turbulent fluxes. Examine the frequency, characteristics and ocean mixed-layer
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for Pollinator Monitoring: Train and optimise deep learning models for pollinator detection and classification using annotated image datasets. Post-processing object tracking algorithms will be incorporated