Solid particles dispersed in a liquid phase at high concentrations (dense) are encountered ubiquitously in industry, found in products ranging from cement and ceramic pastes to slurries for battery and solar panel manufacturing and foods; and in nature, such as mud flows, submarine landslides. The reliable and efficient processing and manufacture of these diverse products presents ‘grand challenges’ to technological innovation because at high solids volume fraction process flow and product behaviour become increasingly unstable and unpredictable. Understanding the rheology and predicting the flow dynamics of such materials also represent grand challenges in fundamental sciences and cutting-edge engineering. The aim for this project is to make step changes in our predictability of dense granular flows in complex geometries and/or loading conditions, and ultimately leading to rational design of novel granular materials through an interdisciplinary approach leveraging recent advances made in multiscale mechanics and machine learning.The students will work in an integrated interdisciplinary environment with researchers in computational mechanics, physics, and a range of engineering disciplines. Specific research topics that are of interest include but are not limited to:•      rheology of dense granular flows in complex geometries, such as converging channels, and/loading conditions, such as cyclic loading;•      rheological constitutive modelling using data driven and machine learning approaches;•      design of rheology through manipulating the particles using electromagnetic, ultrasonic or optical fields or changing particle shape and size distribution or surface tribological properties;•      Interactions between granular particles and biological cells for novel biomedical applications.The candidates should have excellent academic records and relevant experience in Mechanical, Civil, Chemical, Material Engineering, Physics, Applied Mathematics, or other relevant fields.How to Apply: Please refer to the following website for details on how to apply:http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/.