Manufacturing has considerable economical, technological, and environmental importance at the global scale, impacting fields such as transportation, energy, safety, and healthcare. Materials innovation has long relied on costly and ineffective trial-and-error experiments. Meanwhile, computational routes face challenges due to the multidisciplinary and multiscale aspects of linking materials processing, microstructure, and ultimately properties. By building an infrastructure for computational exploration of alloys, this project will put together foundations for computational discovery of structural materials, e.g. by means of high throughput and machine learning methods, which could lastingly change the way we approach metallurgical innovation.

The project will bring together two complementary sets of skills, with a researcher expert in linking materials processing to microstructures, and a supervisor expert in predicting the mechanical behavior of complex microstructures. While adding an essential piece of competence to the host institution, the project will support the growth of the candidate as he aims at building a world-class research group in Europe. He will also gain key skills in software development, and a number of management and transferable skills with the support of  award-winning management and human resources personal (monitored through detailed plans for career development, data management, and exploitation, dissemination, and communication of results).

The impact and reach of the action will be maximized. First, by openly distributing all major components of the computational
framework. Then, with scientific publications in high-impact scientific journals, as well as a broad range of outreach activities
in the form of publications in non-technical outlets, reach out events to young and non-technical audiences, while ensuring
accessibility to the widest possible audience (e.g. through commitment to international accessibility standards).