-
; Nguyen et al., 2023). By integrating large scale, multi-modal data and leveraging self-supervised and transfer learning, these models demonstrate satisfactory spatial-temporal simulation and predictions
-
frameworks that can maximise the performance, efficiency, and emissions reduction potential of such new fuels through intelligent design, modelling, and experimental validation. Research Objectives Investigate
-
to the space-based LISA observatory. The research will advance post-Newtonian waveform modelling through improved analytical techniques, incorporate strong-field information from numerical relativity simulations
-
. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
-
(ED&I) and alternative routes into research. Desirable skills include experience in modelling and simulation (MATLAB/Simulink, Python), energy systems, and intelligent control methods. Applicants should
-
seasonal-to-subseasonal forecasting ensemble in modelling and forecasting these processes. As datasets develop, there may also be opportunities to assess simulation skill of AI forecasts. For further
-
/Simulink/Python for modelling, simulation, and control design. Experience with genset systems, hybrid powertrains, or real-time control applications is highly desirable. A practical interest in system