Sort by
Refine Your Search
-
with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
-
-class facilities, enhancing their skills in materials characterisation, computational modelling, and experimental testing. These experiences will position the graduate as an innovator, ready to
-
mechanism. The integrating should enable to guarantee certain properties of the learned functions, while keep leveraging the strength of the data-driven modelling. Most of, if not all, the traditional
-
unbounded variable and instance sets. In addition, novel approaches such as Physics Informed/Guided Learning allows the learning models to capture the underlying physics/patterns and to generate physically