Fully Funded PhD in Foundational AI & Reinforcement Learning

Laplace Expert Ltd; Greater London; Remote; GBP 21,000 - 26,000; Full time

Job summary

University College London (UCL) invites applications for a fully funded PhD studentship in foundational AI within the Department of Electronic and Electrical Engineering. This 4-year program focuses on reinforcement learning, intelligent data acquisition, and foundation models, with applications across communication systems and scientific discovery.

The project emphasizes rigorous mathematical development, computational experiments, and applied AI research, with a stipend provided.

Qualifications

• UK Master’s degree or an upper second-class Bachelor’s degree, or equivalent international qualification, in computer science, electronic engineering, mathematics, statistics or a related discipline.
• Programming experience is required, preferably in Python and modern machine-learning frameworks.
• Previous research experience or publications are desirable but not required.

Responsibilities

• Conduct rigorous AI research with mathematical development and computational experiments as part of the project.
• Develop and evaluate reinforcement learning and data acquisition methods for foundations models and applications in engineering.
• Collaborate with an interdisciplinary team to publish findings and advance knowledge in AI for communication systems and science.

Skills

Reinforcement learning

Intelligent data acquisition

Foundation models

Python programming

Machine learning frameworks

Sequential decision-making

Generative models

Education

Master's degree or equivalent in CS/EE/math

Job description

University College London (UCL) invites applications for a fully funded PhD studentship in foundational AI within the Department of Electronic and Electrical Engineering. This 4-year program focuses on reinforcement learning, intelligent data acquisition, and foundation models, with applications across communication systems and scientific discovery.

The project emphasizes rigorous mathematical development, computational experiments, and applied AI research, with a stipend provided.