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outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision
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validate signal processing algorithms and stimulation strategies using electrophysiological and behavioral data. Develop GUIs, psychophysical test protocols, and objective outcome measures (e.g., ECAP, ABR
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capabilities such as incorporating new sensors and redesigning the hardware and software prototype. This position is a temporary position that will last 30 weeks from the start date. The University of Minnesota
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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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• Experience in flow cytometry Job Description: This position seeks a highly motivated postdoctoral fellow to investigate how cell death sensors regulate immune responses, with an emerging interest in the retina
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outcomes ●casual representation learning for real-world data ● deep learning interpretation, fairness and robustness ●Regularly conduct computational experiments to execute algorithms on various health and