EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry

We will train a cohort of students at the interface between the physical and computer sciences to drive the critically needed implementation of digital and automated methods in chemistry and materials. Through such training, each student will develop a common language across the areas of automation, AI, synthesis, characterization and modelling, preparing them to become both leader and team player in this evolving and multifaceted research landscape.

The lack of skilled individuals is one of the main obstacles to unlocking the potential of digital materials research. This is demonstrated by the enthusiastic response toward this proposal from our industrial partners, who span sectors and sizes: already 35 are involved and we have already received cash support corresponding to over 27 full studentships. This proposal will deliver the EPRSC strategic priority "Physical and Mathematical Sciences Powerhouse" by training in "discovery research in areas of potential high reward, connecting with industry and other partners to accelerate translation in areas such as catalysis, digital chemistry and materials discovery."

The CDT training programme is based on a unique physical and intellectual infrastructure at the University of Liverpool. The Materials Innovation Factory (MIF) was established to deliver the vision of digital materials research in partnership with industry: it now co-locates over 100 industrial scientists from more than 15 companies with over 200 academic researchers. Since 2017, academics and industrial researchers from physical sciences, engineering and computer sciences have co-developed the intellectual environment, infrastructure and expertise to train scientists across these areas.

To date, more than 40 PhD projects have been co-designed with and sponsored by our core industrial partners in the areas of organic, inorganic, hybrid, composite and formulated materials. Through this process, we have developed bespoke training in data...