AI Techniques for Advanced Materials Design

Description: AI is a rapidly emerging technology with a wide and deep impact. Recently, there have been significant steps forwards in the use of AI techniques such as Deep Learning for the acceleration and enrichment of the materials discovery process. This PhD will work towards further pushing the boundaries of these techniques and applying them in a world-leading materials discovery environment. Particular focus will be on using deep learning to build accurate predictors of physical properties, and on using machine learning to fuse data from simulations and experiments to expand on existing data sources.

Environment: This studentship will be based for at least 6 months at IBM Research UK within the Hartree Center in Daresbury, which was established to transform the competitiveness of UK industry by accelerating the adoption of High Performance Computing, Big Data and Cognitive technologies. Other Hartree focus areas include high accuracy formulation in consumer goods, manufacturing challenges and life sciences projects such as precision agriculture, anti-microbial surfaces and genomics. At the University, the studentship will be based in the Materials Innovation Factory (MIF), a new £68 M research facility, supervised by Prof. A. I. Cooper FRS, the MIF Academic Director. The studentship is funded by EPSRC but will also form a part of the Leverhulme Research Centre for Functional Materials Design, a new £10 M, 10-year activity funded by the Leverhulme Trust.

Qualifications: A 2:1 or higher degree or equivalent in Chemistry with a strong interest in data-science, or alternatively a strong interest in physical science but with Mathematics or Computer Science background. The candidate will be expected to have strong programming abilities (Python preferred), and an interest in the application of machine-learning techniques to complex chemical problems.

Informal enquiries should be addressed to Professor Cooper