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instrumentation package. • Implement real-time signal processing and post-processing techniques to improve recording fidelity. • Design and test hardware on the bench to ensure robustness prior
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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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of the wearable, diagnostic device and signal processing aspects of several world-first multi-modal studies seeking to assess and quantify the effect of repetitive head impacts on short-term and long-term
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aims to provide mathematical models of decontamination processes and is funded by the Defence Science and Technology Laboratory (Dstl). The approach to mathematical modelling is multifaceted, with
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validation to improve understanding and prediction of subsurface processes. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU
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blot, histology, immunohistochemistry), Cardiac cell and tissue culture (incubator), Bioinformatics (transcriptomics, metabolomics, proteomics), Signal processing (optical action potentials, electrograms
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particular emphasis on the intersection between cell signalling and division, using C. elegans. The research project is funded by the BBSRC for three years and is led by Dr Tim Davies. The research will
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passive acoustic monitoring and/or acoustic signal processing, with a preference for candidates with experience in the deployment and recovery of marine acoustic recording systems. Specifically
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USD). Project Description Beyond vision few studies have examined the role of light as signals to regulate development and function of different parts of the body. The identification of Opsin3 (Opn3
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members across electrical engineering, earth science, signal processing, and machine learning to ensure methodological rigor and practical relevance. Qualifications: -Ph.D. in Electrical Engineering