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We have 4 Artificial Intelligence (urban planning) PhD Projects, Programmes & Scholarships

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Artificial Intelligence (urban planning) PhD Projects, Programmes & Scholarships

We have 4 Artificial Intelligence (urban planning) PhD Projects, Programmes & Scholarships

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AI-Driven Digital Cities for Crime Modeling and Economic Analysis

University of Birmingham School of Chemical Engineering
AI-Driven Digital Cities for Crime Modeling and Economic Analysis. Project description. The project aims to develop a methodology for designing AI-driven digital twins of real cities. Read more
 Supervisors: Dr A Alexiadis, Dr T Abadie
 Year round applications  PhD Research Project  Funded PhD Project (UK Students Only)
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Using physics-informed neural networks and data assimilation to predict and improve urban air quality

University of Southampton Faculty of Engineering and Physical Sciences
Supervisory Team.   Sean Symon and Christina Vanderwel. Project description. Read more
 Supervisor: Dr S Symon
 Year round applications  PhD Research Project  Competition Funded PhD Project (Students Worldwide)
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Data-Centric Solutions for Earth Observation Challenges: Developing Cutting-Edge Techniques for Remote Sensing Analysis [SELF-FUNDED STUDENTS ONLY]

Cardiff University Cardiff School of Computer Science & Informatics
In today's data-driven landscape, the importance of data-centric machine learning methodologies cannot be overstated where they prioritize the quality, diversity, and accessibility of data, recognizing that the performance and reliability of machine learning models heavily depend on the data they are trained on. Read more
 Supervisors: Dr O Karakus, Prof P Rosin
 Year round applications  PhD Research Project  Self-Funded PhD Students Only
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Data-Centric Solutions for Earth Observation Challenges: Developing Cutting-Edge Techniques for Remote Sensing Analysis

Cardiff University Cardiff School of Computer Science & Informatics
In today's data-driven landscape, the importance of data-centric machine learning methodologies cannot be overstated where they prioritize the quality, diversity, and accessibility of data, recognizing that the performance and reliability of machine learning models heavily depend on the data they are trained on. Read more
 Supervisors: Dr O Karakus, Prof P Rosin
 6 May 2024  PhD Research Project  Competition Funded PhD Project (Students Worldwide)
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