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change accelerate, we urgently need smart, evidence-based tools to plan, manage, and protect our marine ecosystems. At the forefront of this innovation is machine learning. Its ability to process complex
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on the performance of the CMF; Using machine-learning (deep learning) methods to develop a predictive model and conduct the sensitivity study to investigate the multiple factors on the performance of flow meter
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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of the workflow. While the majority of the project is computer based, there is a small lab-based component in order to generate cell samples to be able to acquire the NMR data. Once proof of concept has been
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
will train machine learning models to identify and assess internal defects with greater accuracy and speed than traditional methods. The results will support predictive maintenance, reduce inspection
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under multiple environmental and socio-economic scenarios. You’ll develop sought-after skills in geospatial analysis, hydrodynamics, sediment transport, machine learning-assisted detection, and hydro
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Software Development: Building the Next-Generation Trust Maturity Model Integrating DevOps practices into ML-driven systems: A Framework and Maturity Model for Continuous Machine Learning Development
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, fairness). Provenance and integrity of machine learning pipelines. Generative content authenticity. Cyber-physical machine learning systems. Scalability of properties from small to large models. In
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econometrics, machine learning, and GIS for predictive housing price modelling Addressing Edinburgh and South East Scotland's Construction Skills shortfall The full description of the projects is available here