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Field
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(e.g. in automotive applications) using, for example, vibration and acoustic signals. Research questions include method development for fault detection and isolation, damage estimation systems, including
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Position Description: We are seeking a postdoctoral researcher specializing in urban modeling and cost analysis to develop an innovative model to estimate the direct and indirect costs
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
Proposed Start Date Estimated Duration of Appointment 12 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching, research and public service, the University
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peer-reviewed journals and conferences. Preferred Qualifications: Experience with black-box modeling of wind turbines and converter-based power systems. Knowledge of Lyapunov-based methods, nonlinear
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photoreceptive pathways using mouse as a model system. Methods used in the lab include various in vitro, ex vivo and in vivo approaches, as well as functional and behavioral studies of relevant opsin knockout mice
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to scientific reproducibility, replicability, and transparency. Key Responsibilities: Research (85-90%) Cell culture management Methods/good laboratory notebook maintenance, documentation, and review Designing
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focus on developing and calibrating new protein sensors of cytosolic metal availability, which underpin the "metalation calculator ", and expand their applications to different microbes. The work
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peer-reviewed journals and conferences. Preferred Qualifications: Experience with black-box modeling of wind turbines and converter-based power systems. Knowledge of Lyapunov-based methods, nonlinear
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experience working with large complex longitudinal datasets is required. (Experience conducting statistical analyses such as robust variance, binomial regression, generalized estimating equations, Cox
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contribute to development of research grant applications. Your profile The applicants should hold a PhD in structural dynamics with focus on data-driven methods (e.g., for input/state/parameter estimation) and