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Field
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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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algorithms for digital health and AI-driven research projects. Lead technical innovation by exploring and implementing emerging AI methodologies. Support data platform development and retrospective data
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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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algorithms for mobile robots. Implement and accelerate visual algorithms for mobile robots on embedded platforms. Develop a visual embedded platform on a mobile robot. Conduct field trials with the robotic
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of algorithms for medical image analysis. The successful candidate will investigate computational complexity, stability, and numerical summaries of multiparameter persistence, as well as applications to medical
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algorithms for fluid-structure interaction solvers What you will do Independently develop numerical methods and codes for fluid-structure interaction of wind-powered ships Carry out and analyse high-fidelity
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data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research, supervise
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polarization states. • Data Analysis & ML: Develop Python/MATLAB machine learning algorithms to map photocurrents to full Stokes parameters, targeting a reconstruction error of \(<1\%\). Required
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orchestration across different network components, as well as to the development of sensing algorithms and ISAC solutions. The postdoctoral researcher will also play an active role in coordinating research