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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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conditions have been satisfied. Project description/summary: This Project will develop a model of material dynamics and heat transfer within a commercial vertical induction heating reactor. This novel reactor
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technological solutions for the recycling of waste heat in specific food industry settings, using computational fluid dynamics modelling, lab experiments and field work To disseminate finding in high impact
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? RMIT Engineering PhD candidates get a laptop, world-class labs, research funding, travel support, and seminars. Join RMIT’s PhD project in non-Newtonian fluid dynamics with a $35,888/year stipend for 3.5
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I offer projects broadly related to supernova explosions and the final stages in the lives of massive stars. Specific topics of interest include fluid dynamics processes in stellar explosions and
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of CO2 propagation in heterogeneous media while accounting for diverse factors that influence flow dynamics. As part of this project the student will undertake a remote internship with Shell to produce