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We have 68 reinforcement learning PhD Projects, Programmes & Scholarships
reinforcement learning PhD Projects, Programmes & Scholarships
We have 68 reinforcement learning PhD Projects, Programmes & Scholarships
EPSRC DLA PhD Studentship: Efficient and Safe Learning within Reinforcement Learning Systems
The project aims to develop a new set of techniques to induce high sample efficiency and safe learning within Reinforcement Learning. Read more
Cooperative Alignment via Multi-agent Reinforcement Learning (S3.5-COM-Loftin)
Deep reinforcement learning (RL) refers to a class of state-of-the-art machine learning algorithms that use deep learning (i.e., neural networks) to solve long-term decision-making problems. Read more
PhD position in reinforcement learning and multi-agent reinforcement learning
The successful applicants will join the University of Edinburgh, Heriot-Watt University, and Leonardo Ltd, one of the UK's leading aerospace companies and one of the biggest suppliers of defence and security equipment to the UK. Read more
Reinforcement Learning-Driven Multi-Agent Information Retrieval Using Large Language Models
This project investigates the integration of multiagent systems and Reinforcement Learning (RL) with large language models (LLMs) to enhance information retrieval and contextual understanding in complex environments. Read more
Optimal and Verifiable Representation Learning for Safe and Efficient Reinforcement Learning Systems
This project explores the integration of calculus of variations with verification-guided representation learning for reinforcement learning. Read more
Agricultural Robot navigation in complex farm and rugged terrain environments using Deep Reinforcement Learning AI (Ref: AACME-24-037)
With increasing global food demands, reducing chemicals and water usage in agriculture is essential. From a UK perspective, climate change and Brexit are the most immediate problems we face in agriculture, with early ripening, and lack of access to seasonal labour being the largest issues. Read more
Enhancing 3D Control of Robotic Limbs Using Brain-Computer Interfaces with Reinforcement Learning
About the Project. The Institute for the Augmented Human at the University of Bath is inviting applications for the following fully funded PhD project, which will commence 29 September 2025. Read more
Achieving Robust Quantum Control through Deep Reinforcement Learning [SELF-FUNDED STUDENTS ONLY]
The success of quantum computing, simulation, and sensing applications hinges on achieving robust control over quantum systems. Read more
Adaptive and robust deep reinforcement learning for drone systems
The increasing complexity of multi-agent systems in robotics has amplified the need for intelligent, cooperative decision-making among agents. Read more
[Sys2RL] Thinking, Fast and Slow: Leveraging Reinforcement Learning to Improve Decision-Making in Generative Models
AI_CDT_DecisionMaking. Details. Generative models, such as large language models (LLMs), have exhibited remarkable success in generating coherent text, mimicking human-like conversations, and completing complex language tasks such as translation and summarization. Read more
Dexterous Manipulation for Hybrid Robots Using Reinforcement Learning
Research Group:
Intelligent Systems and Robotics
Hybrid Robotic manipulators combine soft and rigid components that allow them to be safer and more reliable than their rigid counterparts during their interactions with the world. Read more
Agent-Based and Machine Learning Models for understanding the Economic Impacts of AI and/or the Green Transition
Research Focus. Economies worldwide are undergoing transitions driven by new technologies and the move toward a green economy. These transitions, if not done carefully managed, can increase inequality and political polarisation, but under the right policies they can contribute to a more equitable and prosperous future. Read more
Multi-agent Deep Reinforcement Learning Assisted Vulnerability Assessment and Defense Framework for Digital Twin-Enabled Industrial Systems (S3.5-COM-Pasikhani)
As industries adopt automation and digital twin technologies, they become increasingly vulnerable to sophisticated cyber-attacks. Read more
GEMS Topic: AI-Driven Incidental Detection of Unruptured Intracranial Aneurysms: Development of a Multi-Agent Reinforcement Learning Tool for Enhanced Neuroimaging
Incidental detection of unruptured intracranial aneurysms (UIAs) has become more critical with advancements in imaging technologies. Read more
Deep learning of deformable object manipulation on manufacturing robots
Background. Current robots in manufacturing settings are not able to adapt to variations introduced by collaborating humans or other factors in the environment. Read more