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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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particular: Design algorithm for localization using ultrawide band (UWB) sensors. Conduct experiment, collect data, and analyze results. Simulate and evaluate system performance. Document research outcome to
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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
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on the aptitude of the candidate(s), the project could be oriented on the instrumentation and the development of signal processing algorithms, time series data processing and modeling, statistical analysis and
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, management information systems or Computer Science. Six years of work experience in foundational computer science areas: algorithms; computer architecture; programming methodologies and languages; data
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algorithms for real time neural signal processing. Proficient in a range of machine learning techniques, including neural networks, with particular experience in real-time debugging of algorithms during live
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Postdoctoral Research Fellow to work on the design, development, and realization of future communications technologies. You will be part of the team and contribute to ongoing developments in theory, algorithms
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large quantities of data to gain a greater understanding of our systems and develop data analytics and artificial intelligence algorithms. You will be actively engaged in the research and development
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discipline. At least 3 first author papers in disciplines related to neuroprosthetics. Published first author work in using machine learning algorithms for real time neural signal processing. Proficient in a
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation