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Field
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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
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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on using unstructured and overset meshes with high-fidelity algorithms to obtain scale-resolved data. Candidate will also post-process data using data-driven and physics-driven methods to extract fundamental
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anthropogenic impacts on these elements. The scale of the project will be at different levels from case study and country level to continental and global level. Work duties You will primarily devote yourself
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, physics, or a medical imaging related field. Experience with developing advanced pulse sequences or accelerated acquisition and reconstruction algorithms will be highly valued. Interested candidates should
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of Applied Psychology. Current faculty conduct research on a wide range of topics pertaining to the future of work, including entrepreneurship, collaboration, remote working, labor markets, algorithms, machine
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interdisciplinary liberal arts curriculum in rhetoric, communication, and media studies. Areas of focus might include, but are not limited to, algorithms, AI, infrastructure, extended reality, information science
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are searching for a motivated PhD candidate to design practical over-the-air computing algorithms and protocols for future edge AI applications. About the employer The research of this PhD position will be
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Background Investigation Statement: Prior to hiring, the final candidate(s