Postgraduate research project

AI directed materials discovery and atomistic modelling

Funding
Competition funded View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

This project focuses on developing chalcogenide glass materials using group VI elements such as sulfur (S), selenium (Se) and tellurium (Te), for advanced optical, photonic, and electronic applications. 

We create these using the unique processes developed at the Novel and Compound Glass facilities within the Zepler cleanrooms. The properties of these amorphous semiconductor materials ensure a very wide transparency range, spanning from the visible to the far infrared, thus giving rise to numerous potential industrial applications.

However, the synthesis of these materials is often complex and capital intensive, as they are typically combined with rare and expensive elements including Germanium (Ge) , Antimony (Sb) or Gallium (Ga). Therefore, in parallel with experimental activities, modelling and simulations will form a significant aspect of your research by developing cutting edge knowledge and expertise with the burgeoning range of AI tools available for materials discovery at the atomistic level to use earth abundant elements and thus develop the next generation of advanced materials with extraordinary properties.  

Research involves both experimental fabrication in Zepler cleanrooms and artificial intelligence (AI) and machine learning (ML) driven simulations to design materials using earth-abundant elements. You will develop highly transferable skills in cleanroom sample fabrication  and electronic and photonic device characterisation, materials processing, numerical simulations and machine learning with input from industry partners and working with leading academic experts.