Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
CSIRO IPhD Scholarship - Investigating the interactions between sulfide minerals and in-situ recovery fluids for sustainable copper mining The CSIRO Industry PhD Program (iPhD) is a four-year
-
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
-
treatment of impurities Experimental work to develop comprehensive understanding of iron ore solubility in molten carbonates Characterisation of iron deposits formed in the presence of various impurities and
-
that can flow without resistance, mimicking the behaviour of quantum fluids. These systems, known as quantum fluids of light, promise revolutionary applications in low-energy photonic devices, including
-
that can flow without resistance, mimicking the behaviour of quantum fluids. These systems, known as quantum fluids of light, promise revolutionary applications in low-energy photonic devices, including
-
future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
-
research, including experimental design, execution and manuscript writing across multiple projects. The path to Adelaide University We are on an exciting path to Adelaide University as we prepare to open our
-
Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
function of these cell envelopes for several bacterial species. The most powerful models have several parameters set from experimental observations, in this case data gathered through the use of electron
-
Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
-
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