-
, and advanced machine learning in the engineering domain. Generative AI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase
-
aspects of machine learning. Applications include improving the efficiency of data assimilation methods and understanding why and how deep learning works. Applicants should have, or expect to achieve
-
to also improve and scale the process. We have made major contributions in this area, including the use of Machine learning to discover new cryoprotectants [Nature Communications 2024, 15, 8082
-
sluggish diffusion kinetics of HEAs make them excellent candidates for resisting oxidation and corrosion in high-temperature steam. Guided by thermodynamic modelling and machine learning, we will identify
-
overseas. Training can be provided in computational fluid dynamics, machine learning, and nonlinear dynamics. These skills are highly valued across a wide range of industries. Recent data reveals that Fluid