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goal is to facilitate regional and global impact through innovation in energy materials, advanced energy technologies and smart energy systems. To learn more about this important work, please visit here
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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spectroscopic techniques, theoretical modelling, and precise synthetic control – have significantly improved the activity, selectivity, and stability of CO₂-to-alcohol conversion. Key catalyst systems include Cu
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. This position will focus on one key stream: understanding and improving the interaction between EVs and roadside barriers. This will involve: Modelling EV crash dynamics with conventional and SRB barriers
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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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contribute to research and policy addressing the escalating issue of the consumption of image-based sexual abuse (IBSA) and child sexual exploitation material (CSEM) online. The project is based at Flinders
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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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symptoms. Alexithymia is a major focus of our lab's research, whereby we have created new theoretical models of alexithymia (the attention-appraisal model of alexithymia; Preece et al., 2017), new
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Characterization Techniques Study the advanced electrochemical characterization methods. Gain deep insights into the reaction models associated with PCFCs. 3) Understanding of Electrocatalytic Performance and
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organic nanomaterials for future electronics, optoelectronics and spintronics" "Light-transformed materials" "Theoretical and numerical modelling of the electronic structure of functional low-dimensional