physics-informed neural networks

Are you passionate about solid mechanics and intrigued by machine learning? We are seeking a qualified candidate who can merge expertise from both fields to develop innovative tools for analyzing deformation and fracture in solid materials.

Expected start date and duration of employment

This is a 1-year position starting on 15 August 2025 or as soon possible thereafter.

Job description

Link to the paper - PINN-Poroelasticity

If you are interested in physics informed neural networks (PINNs) and coupled single and multiphase flow in porous media, please check out our work below: 

- We find it challenging to solve coupled poroelasticity relations using PINNs (data-free).