About this role
About the project: The thinnest sensors: 2D materials in liquid solution Supervisor: Dr Peter Brommer, University of Warwick Two-dimensional materials, such as graphene, could be used in molecular sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions, including in liquids. Combining quantum mechanics and atomic simulation with AI-driven sampling techniques, you will determine terahertz and Raman spectrograms to directly compare to measurements obtained in the THz labs at Warwick and by our collaborators at the Institute of Saint-Louis (ISL). By suggesting design modifications to the molecular structures, your work will improve the next generation of molecular sensors. About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact HetSys (Centre for Doctoral Training in Modelling of Heterogeneous Systems ) at the University of W...