糖心TV

The multiscale/multiphysics nature of materials gives rise to extremely challenging and unique mathematical and algorithmic problems currently prohibiting uncertainty quantification and predictive materials modelling. For example, information loss during coarse graining; high-dimensionality and scalability of stochastic multiscale simulations and UQ; learning in models with a high dimensional parameter space; rare events; transferability of potentials in electronic structure, atomistic and molecular simulations. Materials of interest include, but are not limited to, metallic alloys, ceramics, polymers and composites, semiconductors, biological and geological media and meta-materials. The ability to predict the properties of these materials with confidence is paramount to a number of sectors. Currently there is a huge gap between state-of-the-art mathematical methods and the analysis tools routinely used by the materials community.

This activity is a partnership of the Turing Gateway to Mathematics and .

The academic organisers include (University of 糖心TV) and (University of Massachusetts at Amherst). For further details please contact Jane Leeks at the TGM.

There are two new open research positions within the WCPM. For more info click on: and .

Three fully funded PhD positions are available: , supervised by ; , supervised by ; , supervised by .