A fully funded PhD studentship covering UK home fees and a London stipend of £20,662 per annum for 3 years is available for a starting date in September 2024. The student will be supervised by Dr. Yongxin Yang in the school of Electronic Engineering and Computer Science of the Queen Mary University of London. This project sits at the intersection of machine learning and quantitative finance, with a focus on advancing areas such as derivatives pricing and portfolio optimization. The research may extend established studies like option pricing and index tracking or explore some new topics (e.g., agent-based market simulation). The successful candidate will harness advanced techniques including Large Language Models (LLMs), AI Agents, Neural Differential Equations, Self-Supervised Learning (SSL), Neural Implicit Representations (NIR), and Meta Learning, with an emphasis on creating accurate, robust, and trustworthy models. The goal is to develop accountable machine learning tools that can be adopted by the finance industry, and promoting open-source research in quantitative finance.