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technology. About You You may come from a range of backgrounds in theoretical physics or mathematics, with expertise aligned to the goals of the QuRMIT Theory Lab and the Future Fellowship project. We
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. Knowledge in Advanced Physical Models such as the ones typical used in Many Body physics, Superconducting Quantum field theories and RF Quantum Optics. Interests in Exploring novel kinds of Quantum Sensors
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experience in at least one of the following would be highly regarded: (i) the theory and simulation of scattering, diffraction and imaging with high energy electrons or X-rays; (ii) solving inverse scattering
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Macquarie University, Wallumattagal Campus, North Ryde • Supportive and collaborative team with hybrid working arrangements About the role We are seeking a highly motivated and suitably qualified Postdoctoral
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Factors theory and application in health systems. About Monash University Join Monash University’s dynamic research environment at the Alfred precinct, where ground-breaking translational medicine meets
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implementation science. We are now seeking an exceptional Research Fellow (Level B or C) to lead innovative methodological research in statistical theory for adaptive variants of longitudinal cluster randomised
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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encouraged. About the Role Reporting to the Bradley Distinguished Professor, you will be responsible for undertaking high-quality research projects deploying de-colonising theory and practice, to build and
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industry, policy, and public sectors Review relevant literature and engage with sociological theory to understand the role of “cute” home helper robots in Australian households Undertake design and digital
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming