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collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation Qualifications: An earned PhD
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collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation Qualifications: An earned PhD
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of an algorithm to analyse discharge signals, building a secure dataset for new tool–workpiece material combinations enabling process-integrated antibacterial coatings, derivation of data-based strategies to reduce
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external organizations, as well as publishing work in scientific journals and presenting work at conferences. Implement software algorithms in C++ and Python in a collaborative environment. Work closely with
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and other external organizations, as well as publishing work in scientific journals and presenting work at conferences. Contribute to the first principles problem formulations, algorithm development
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information theory: designing and analysing error-correcting codes, establishing fundamental performance limits, and building practical decoding algorithms and architectures. Your research will sit at
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system that integrates EEG, camera footage, and physiological signals; (b) develop and implement algorithms for signal processing and user intent decoding; (c) work with a Generative AI (GenAI
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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, operational, and societal constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms
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and build a light-sheet encoded-illumination microscope Characterize the system Sample Chamber Development Development of Decoding Algorithms Single-Plane SR Imaging Volumetric Imaging of selected