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James Kermode is a Professor of Materials Modelling in the School of Engineering at the University of Warwick. He currently serves as the Research Cluster Leader for the Predictive Modelling research cluster and directs the EPSRC Centre for Doctoral Training in Modelling Heterogeneous Systems (HetSys). Kermode's research focuses on the development of multiscale materials modelling algorithms, with a particular emphasis on machine learning and data-driven approaches. His work quantifies uncertainty in output from electronic structure and atomistic models, and he actively applies parameter-free modelling techniques to make quantitative predictions about chemomechanical materials failure processes. He has contributed significantly to understanding the interactions between dislocations and atomic-scale impurities in materials and is known for his innovative approaches to modelling plasticity and crack propagation in materials such as nickel-based superalloys. His extensive publication record includes notable articles in journals such as Nature Communications and Physical Review X, where he has explored interatomic potentials and the implications of stress on material behavior.
University of Warwick • Coventry
Leading research in materials modelling and predictive techniques.
University of Warwick • Coventry
Research and teaching in the field of materials engineering.
University of Warwick • Coventry
Engaged in advanced materials simulations and modelling.
University of Warwick • Coventry
Conducted research in materials science and engineering.
King's College London • London
Focused on materials modelling and simulations.
University of Cambridge • Cambridge
Worked on engineering modelling and analytical techniques.
Includes General, Mechanical, Civil, Electrical, Biomedical, and Manufacturing Engineering. Most programs fall under English Band A.