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nonlinear and non-Gaussian estimation techniques and data assimilation. Familiarity with hypersonic systems, GNC, or aerospace autonomy. Nonlinear/non-Gaussian estimation, MTT, PHD filters. Deep understanding
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, including but not limited to AI; analyzing user behaviors, perceptions, and learning outcomes with computational and/or mixed methods; and publishing in major conferences and journals in information and
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. Experience with dye tracing and tracer methods in groundwater studies. Experience mentoring graduate or undergraduate students. Experience with machine learning techniques. Experience with field-based
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calcium imaging. Project topics include investigations into the effects of early stress, as well as aversion- and reward-based systems. A willingness to learn new techniques is essential for success in
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spearhead technical development, data analysis, and publication efforts for a student-led initiative using OpenBCI hardware, EEG recordings, eye-tracking integration, and machine learning to enhance neural
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equipment regularly and help oversee a lab to conduct experiments safely Knowledge, Skills, and Abilities Willingness to learn new skills outside of current discipline and comfort zone to accomplish project
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statistics and fMRI data analysis, as well as basic knowledge in, or willingness to learn about, the psychology of aging. Minimum Qualifications Ph.D. in Psychology, Neuroscience, or a related field at the
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optical cavities, interferometry, linear photodetection, and low noise radio-frequency noise analysis is required. Experience with cryogenics and nanofabrication is a plus. An option to co-teach the 5
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laboratory settings; acquire and process airborne and satellite remote sensing datasets; ground-truth remote sensing data; analyze geological samples via petrography, geochemistry, and hand sample analysis