Sort by
Refine Your Search
-
, in collaboration with Rolls-Royce, will develop innovative coatings to safely contain hydrogen in critical aerospace materials through experimental and computational modelling work. You’ll join a
-
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
-
be used effectively as a performance digital twin to generate high-quality engine performance models and produce required training data for the proposed project. This could be a good starting point for
-
The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
-
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
-
of big data might not be possible to be captured by traditional modelling approaches. This implies that mathematical modelling of such data is infeasible. The data-driven modelling approach could resolve