440 postdoc-computational-fluid-dynamics-"Prof" positions at Monash University in Australia
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gases" "Ultrafast dynamics of quantum matter" "Interactions between strongly coupled light-matter quasiparticles" "Atomically thin materials coupled to light" "Periodically driven many-body systems" web
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theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
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" "Searching for physics beyond general relativity with gravitational-waves" (with Prof Paul Lasky) "Improving the sensitivity of gravitational-wave detectors" (with Prof Paul Lasky) "Detecting dark matter with
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known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
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between theoretical and computational high-energy physics. The research contributes to the world-leading PYTHIA Monte Carlo Event Generator, which serves as the baseline for the majority of experimental
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of neutron stars); stellar rotation of misaligned systems (internal rotation evolution, binary and multiple stars dynamics and interaction). Please feel free to come by my office or drop me an email if you
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stars using stellar evolution" (with Prof Ilya Mandel) "The impact of new carbon burning rates on the AGB-supernovae mass boundary" (with Prof Alexander Heger) "The connection between novae and Type Ia
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My research focuses on the theory of strongly correlated phenomena in cold atomic gases and electron systems. Particular topics of interest include low-dimensional quantum systems, superconductivity and quantum impurities. I was previously part of the Australian Centre of Excellence for Future...
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the next generation of standard models with GAMBIT" "Using the Higgs boson to search for dark matter particles and other new physics" "Detecting dark matter with the Cherenkov Telescope Array (with Prof Eric
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Dowe, 1999a) ensures that - at least in principle, given enough search time - MML can infer any underlying computable model in a data-set. A consequence of this is that we can (e.g.) put latent factor