Postdoc Artificial Intelligence for the Dynamics of 2D Materials

We live in an era where artificial intelligence (AI) stands as a beacon of innovation, where advances in machine learning (ML) profoundly impact many aspects of our society. Nevertheless, the use of ML in engineering is still in its infancy. Many areas of engineering that could leverage on ML include (meta)material characterization and design, computational structural design, and symbolic regression (i.e., obtaining mathematical expressions from experimental data), to name a few. At Delft University of Technology we recognize the immense potential AI holds in revolutionizing a broad range of engineering problems.

In this project we will look at ultra-thin materials, which are at the forefront of technological development due to their extraordinary properties. Graphene, for instance, stands as the strongest, most impermeable, and conductive material known to date. There is a myriad of applications where graphene could find its way. However, the materials’ extreme noise sensitivity gives rise to a plethora of poorly-understood phenomena. Through the use of ML, we will derive precise mathematical expressions that describe the behavior of these materials in the presence of noise, paving the way for unleashing their full potential for extreme sensing in high-tech industries such as aerospace and medical.

As a postdoctoral researcher your tasks will include:

• Developing on "deep symbolic regression", i.e., an existing ML framework that uses neural networks to determine mathematical expressions from experimental or numerical data.
• Coordinate the work of related MSc projects.
• Help with writing proposals to secure further funding for this topic.
• Publishing in renowned journals, and presenting your research at international meetings.