game PhD Projects, Programmes & Scholarships for Self-funded Students

We have 53 game PhD Projects, Programmes & Scholarships for Self-funded Students

Towards Trustworthy and Responsible LLMs through Verification and Validation

University of Southampton Faculty of Engineering and Physical Sciences

The emergence of Large Language Models (LLMs) is now transforming the landscape of Natural Language Processing (NLP) and multimodal applications as we speak. Read more

Supervisor: Dr Y Dong

Year round applications PhD Research Project Competition Funded PhD Project (Students Worldwide)

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Collaborative probabilistic machine learning

The University of Manchester Department of Computer Science

We develop probabilistic machine learning methods for helping other agents make better decisions, ultimately human agents in ongoing applications in science and engineering. Read more

Supervisor: Prof S Kaski

Year round applications PhD Research Project Competition Funded PhD Project (Students Worldwide)

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Intelligent and Efficient Testing and Verification of Deep Neural Networks

University of York Department of Computer Science

About the Project. Deep Neural Networks (DNNs) have demonstrated human-level capabilities in several challenging machine learning tasks including image classification, natural language processing and speech recognition. Read more

Supervisor: Dr S Gerasimou

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

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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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Artificial Intelligence - Computer Vision

Rochester Institute of Technology USA Department of Computing and Information Sciences

Our research efforts aim to understand the nature of visual perception so that we can create more visually intelligent machines. This is enabled via fundamental concepts in reasoning, prediction, supervised, semi-supervised and unsupervised learning, and stochastic optimization techniques. Read more

Supervisor: Prof PS Shi

Year round applications PhD Research Project Funded PhD Project (Students Worldwide)

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