ASSISTANT OR ASSOCIATE PROFESSOR (AI-ACCELERATED MESOSCALE MATERIALS MODELLING)

Women's Engineering Society; United Kingdom; On-site; GBP 50,000 - 70,000; Full time

Job summary

Women's Engineering Society in Warwick seeks an Assistant or Associate Professor in AI-accelerated Mesoscale Materials Modelling. This role involves pioneering research relevant to the UK's industrial strategy and the AI-for-Science agenda. The successful candidate will teach courses such as Finite Element Analysis and will work closely with various research clusters. Ideal applicants will have a strong background in AI-driven modelling techniques and a commitment to high-quality education.

Qualifications

• Demonstrated experience in AI-accelerated mesoscale modelling.
• Expertise in data-centric engineering and uncertainty quantification.
• Ability to teach undergraduate and postgraduate programmes.

Responsibilities

• Contribute to research in mesoscale modelling of materials.
• Engage in high-quality teaching for engineering programmes.
• Collaborate within experimental and theoretical research groups.

Job description

ASSISTANT OR ASSOCIATE PROFESSOR (AI-ACCELERATED MESOSCALE MATERIALS MODELLING)

The School of Engineering invites applications for an Assistant or Associate Professor position in AI-accelerated Mesoscale Materials Modelling in the Predictive Modelling research cluster within the School of Engineering, University of Warwick. The post is on the Research and Teaching Pathway.

The successful applicant will pursue research that makes fundamental contributions to mesoscale modelling of materials while addressing real-world challenges of direct relevance to UK industrial strategy and the AI-for-Science agenda. We are particularly interested in AI-accelerated approaches that strengthen mesoscale modelling itself, for example surrogate models, data-centric engineering, and Bayesian techniques for uncertainty quantification and addressing model mis-specification, rather than AI/ML applied without a mesoscale modelling base. Applicants should demonstrate how their work complements the existing atomistic and quantum-scale strengths of the Predictive Modelling Cluster and how it can connect to experimental groups in the Quantum Devices, Multiscale Materials, and wider electronic and power-electronics communities within and beyond the School of Engineering.

Consideration will also be given to alignment with the University’s Research Technology Platforms, the Scientific Computing RTP, and the Warwick Centre for Predictive Modelling (WCPM). We are especially interested in candidates whose work can leverage or contribute to the School’s collaborative, translational, and industrially engaged research environment.

Candidates will be expected to teach to the highest quality on undergraduate and postgraduate programmes offered by the School of Engineering, including Finite Element Analysis for structural mechanics.