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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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PhD Scholarship for a Design-Led Research Program on the Future of CT Imaging in Distributed Care Job No: 680923 Location: Caulfield campus Employment Type: Full-time Duration: 3-year fixed-term
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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. #sustainability Project description For distributed renewable micro-grids to become a mature technology, the economics and the reliability have to be equal to or better than today’s distribution grids. The PhD
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Algorithmic systems
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In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
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-preserving trustworthy distributed machine learning. In this research, the successful candidates will focus on mathematical backgrounds involved in differential privacy to devise novel scalable approaches
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opportunities for advancements in the entire hydrogen value chain, including production, transport, and distribution. The transportation of hydrogen to consumers poses a significant challenge, and the current gas
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Mixed-Integer Programming (MIP) solvers are very powerful tools to solve combinatorial problems that arise in many industries. Modern MIP solvers usually run a sequence of algorithms to solve
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to contemporary challenges while mentoring the next generation of leaders. Building on its strong foundation in Optics and Photonics, EECS is expanding its research into quantum algorithms and their industrial