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. Experience in organic synthesis focused on methods development and/or catalysis. Preferred Qualifications: Candidates are expected to have a strong synthetic organic background, preferably with experience in
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. Traditional small-signal stability analysis methods are insufficient for evaluating large disturbances such as faults and disconnections. This project focuses on developing and validating computationally
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a multidisciplinary research team focused on developing energy-efficient and fault-tolerant AI systems that can operate reliably in the radiation-rich environment of space. The project integrates
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Siemens Prisma Fit (and additional 3 T systems if desired) to collect structural and dynamic MRI data. * Quantitative analysis: develop pipelines for dynamic MRI and physiologic data; integrate multimodal
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sequence implementation: operate a 3 T Siemens Prisma Fit (and additional 3 T systems if desired) to collect structural and dynamic MRI data. ● Quantitative analysis: develop pipelines for dynamic MRI
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sequence implementation: operate a 3 T Siemens Prisma Fit (and additional 3 T systems if desired) to collect structural and dynamic MRI data. ● Quantitative analysis: develop pipelines for dynamic MRI
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(INCUS) and the Atmosphere Observing System (AOS) missions. The radar science group is also a university partner to the development of the new Airborne PAR for the National Center for Atmospheric Research
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of Convective Updrafts (INCUS) and the Atmosphere Observing System (AOS) missions. The radar science group is also a university partner to the development of the new Airborne PAR for the National Center
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a multidisciplinary research team focused on developing energy-efficient and fault-tolerant AI systems that can operate reliably in the radiation-rich environment of space. The project integrates
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of Convective Updrafts (INCUS) and the Atmosphere Observing System (AOS) missions. The radar science group is also a university partner to the development of the new Airborne PAR for the National Center