Lloyd completed his PhD research in the Plasma Physics Group, working on theoretical and computational dusty plasma physics. His thesis work related to the basic physics of dust-plasma interactions in tokamak fusion plasmas.
His work demonstrating that strong magnetic fields significantly modify the ion drag force on macroscopic impurities in tokamak plasmas was an Editors Pick published in Physics of Plasmas.
In 2020, Lloyd received the Department's Malcolm Haines Prize for Outstanding Young Plasma Physicist.
Lloyd has contributed to Computing teaching in the Physics Department, winning College funding for, and leading the development of an online resource that gives students the opportunity to practice computational physics techniques in Python, called PyProblems.
Lloyd has a number of years of experience with data science and machine learning techniques, and has contributed to work applying a machine learning approach to dust tracking in tokamaks.
et al., 2020, Robust impurity detection and tracking for tokamaks, Physical Review E, Vol:102, ISSN:2470-0045
James L, Coppins M, 2020, Suppression of the ion drag force on dust in magnetized plasmas, Physics of Plasmas, Vol:27, ISSN:1070-664X, Pages:1-9
et al., 2020, A study of the propagation of a solitary wave along the magnetic field in a cold collision-free plasma, Physics of Plasmas, Vol:27, ISSN:1070-664X