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Improving fleet-based decision-making with causal artificial intelligence (S3.5-MAC-Hughes) School of Mechanical, Aerospace and Civil Engineering PhD Research Project Competition Funded Students
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Life cycle assessment of renewable chemical production with artificial intelligence School of Chemical, Materials and Biological Engineering PhD Research Project Directly Funded UK/EU Students Dr
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
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traditional data analysis techniques. Additionally, the project will explore potential applications of TDA in artificial intelligence, emphasizing the significance of integrating these techniques in broader AI
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. Additionally, the project will explore potential applications of TDA in artificial intelligence, emphasizing the significance of integrating these techniques in broader AI contexts, which is increasingly
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combining two exciting areas of research: 3D human modelling and large-scale artificial intelligence systems known as “foundation models.” The first step will be to create accurate 3D models of the human body
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leverage the recent advances in the implementation of artificial intelligence in drug discovery to develop an accelerated workflow for the discovery and experimental validation (synthesis and evaluation
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noisy real-world data against which to test the developed methods. This is a project at the intersection of mathematics, control theory, and artificial intelligence, with strong opportunities
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evidence resides across unstructured notes, patient records, medical literature, and intricate clinical protocols. Recent advances in Artificial Intelligence (AI), leading to the development of Large
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at the University of Sheffield. Artificial intelligence tools are increasingly used across many industries, with large language models (LLMs) such as ChatGPT emerging as particularly powerful tools for software