London, England, United Kingdom
Theoretical physicist working on condensed matter field theory and machine learning for theoretical physics. PhD candidate at University of Iowa, working with Prof. Michael Flatté. Based at the London Centre for Nanotechnology (UCL) in a long-term visiting position, collaborating with experimental and theoretical condensed matter groups. I specialise in quantum field theory applications to materials and devices, using analytic approaches, computational methods (AFQMC, tight-binding, CI) and machine learning. My current focus is on the effects of disorder on semiconductor quantum computing architectures and the application of neural network surrogates for effective field theory. Seeking 2026 positions bridging machine learning and physics, in academia or industry. 📍 London, UK | 🎓 University of Iowa
Long-term visiting position conducting research at the intersection of quantum field theory and nanoscale device physics. Working on quantum transport in delta-doped layers for quantum information applications, in collaboration with experimental and theoretical groups at the LCN. Also exploring applications of deep learning to condensed matter field theory, particularly for modelling dynamical properties of materials.
Responsible for the research and development of a novel cooling system that would allow for sub 15 minute charging times.