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

Transforming the Future: AI-powered Sustainable solution to enable fast response to dangerous pollution levels for a breathable tomorrow

Kingston University Faculty of Engineering, Computing and the Environment

The research project aims to construct an autonomous computational system using purposeful AI (ML, Deep Learning) that continuously collects and analyses datasets from various sources (e.g. Read more

Supervisor: Dr F Rahman

Year round applications PhD Research Project Self-Funded PhD Students Only

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Virtual Reality and Safety Training: an evolutionary approach to enhancing hazard perception in cycling communities

Anglia Ruskin University ARU School of Engineering and the Built Environment

Proposed supervisory team. Dr Shabnam Sadeghi Esfahlani. Dr Matthew A. Timmis. Dr Kjell van Paridon. Theme. AI, Robotics and Automation. Impact themes. Read more

Supervisor: Dr S Sadeghi-Esfahlani

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 [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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