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research team and support us in our efforts to develop refined preclinical models for high-impact emerging viruses. You will be directly contributing to global pandemic preparedness efforts in a One Health
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Modeling, Musculoskeletal Modeling, Wearable Sensors All offers of employment are contingent upon successful completion of a background check. The University of Oregon is proud to offer a robust benefits
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builds on an established platform and focuses on measurable performance gains, traceable calibration, and demonstrated stability under realistic operating conditions, with a clear route to industrial
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-month PostDoc position in modelling land-cover change at watershed-scale. Project Overview Deep-C brings together a consortium of experimentalists and modelers to explore the coupled carbon (C) cycling in
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modelling of the impact of precipitation on mm wave fixed radio links from the high-end weather station installed at Durham University and measurement data. The successful candidate will be working in
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mathematical modelers and statisticians to perform data analyses. This work will include working with influenza viruses, rhinoviruses, and human coronaviruses. Responsibilities Include: Research- 75% • Perform
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 4 hours ago
: Tailoring the phase-matching conditions to generate entanglement across various degrees of freedom (polarization, time-energy, or frequency). Robustness Characterization: Evaluating the source performance
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material performance. The postdoctoral researcher will investigate ammonia-controlled co-precipitation of precursor materials and study how impurities such as Li⁺, Na⁺, F⁻, Mg²⁺, Cu²⁺ and Al³⁺ influence
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academic institutions. Individual will develop and test novel computational models of the neural activity generated by electrical stimulation of the brain. Also, perform data analysis utilizing medical
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diagnosis of gas turbines. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components