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environmental degradation and economic strain. Existing detection methods fail to address the issue effectively, being both costly and unreliable. This project proposes an innovative solution by integrating drone
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The University of Stirling invites applications for up to three PhD positions in Applied Economics within the Applied Economics Lab, a vibrant research cluster in the Economics Division of Stirling
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or existing tools into an effective pipeline. Highly collaborative, good communicator, able to find solutions to problems, to work effectively as part of a team. Creative thinker, able to contribute
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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optimisation, industrial exposure, or soft skills including presentation skills, project management, and communication skills. There are also numerous employability opportunities that the PhD will offer whether
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by for example, exploiting differences in pH occurring between storage/usage and post-use in the environment, or by specifically engineering biodegradable sites into the chemical substitutions. To find
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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integrating Machine Learning (ML) with physics-based degradation modelling will enhance early fault detection, reducing unplanned downtime. This PhD is hosted at Cranfield University, a global leader in
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. The successful candidate will also have the opportunity and be expected to develop and conduct their own PhD research on how racism creates epistemic injustice and restricts formal and informal carers