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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Multi-agent systems: distributed intelligence
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to the advancement of healthcare technologies, systems, and services through applied design practice. With a portfolio spanning mobile imaging, wearable technologies, and distributed models of care, DHC leads
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response incentive arrangements with the national electricity market (NEM). Currently cost recovery for regulation frequency services is based on the causer pays process, which allocates the cost of sourcing
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care. There is evidence that clinical debriefing models can mitigate the psychological effects of these stressful events and improve the psychological safety of their working environment to improve
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The PhD candidate will gain intensive knowledge in innovative processing protocols for chemical sensing and to develop data acquisition system with the Machine Learning (ML) and/or Deep Learning (DL
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models at many scales including electron dynamics, soft-matter physics, materials-biomolecules interaction and device physics exploiting the collaboration with a multidisciplinary team of theoreticians and
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This scholarship is jointly funded by a leading computer vision company in Australia and the STEM College of RMIT University. The research includes investigation into automated product quality
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process from biomass. In the PhD program, you will be involved in working with a multi-disciplinary team. You will be conducting experiments and developing phenomenological models to understand the graphite
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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