PhD in Optimisation

Data-driven predictions of dynamical systems are used in many applications, ranging from the design of products and materials to weather and climate predictions. The aim of this project is to exploit techniques from the data-driven pde community to design new methods to identify geometric dynamical systems, while tackling the uncertainty quantification task and the high-dimensional and noisy data regime. We are looking for an enthusiastic and highly motivated graduate with relevant background in at least one of the fields of machine learning, numerical analysis, optimisation, or related fields.