This PhD project at The University of Manchester focuses on accelerating neutral particle transport simulations using artificial intelligence. State-of-the-art Monte Carlo simulations are essential for modeling nuclear reactors (both fission and fusion) and radiation shielding, but they are among the most computationally demanding tasks in science. The project aims to leverage advances in AI and machine learning to significantly improve the efficiency and accuracy of these simulations, with potential applications in nuclear physics, medical physics, and space science. As part of the Department of Physics and Astronomy, you will join a vibrant research environment and work under the supervision of Professor SB Boogert. The research will involve developing and applying novel AI-driven algorithms to complex stochastic processes, integrating computational mathematics and engineering mathematics with cutting-edge physics research. You will have the opportunity to collaborate with interdisciplinary teams and contribute to advancements in both fundamental science and practical engineering applications. Applicants should have a strong background in physics, mathematics, computer science, or a related field, with experience in computational methods and programming. Familiarity with machine learning, artificial intelligence, or Monte Carlo techniques is highly desirable. The project is suitable for candidates interested in pushing the boundaries of computational physics and exploring innovative solutions to real-world scientific challenges. The application deadline is 5 December 2025. For more information and to apply, visit the project page on FindAPhD or The University of Manchester's postgraduate application portal.