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9738BR Kate Gleason College of Engineering KGCOE Mechanical Engineering Job Summary The Fluid-Acoustic-STructure (FAST) laboratory at Rochester Institute of Technology (RIT), directed by Dr. Byron D
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Pipsa Saharinen’s research group at the Translational Cancer Medicine Research Program at the Faculty of Medicine, University of Helsinki and Wihuri Research Institute invites applications
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commitment to interdisciplinary research are especially encouraged to apply. Responsibilities will include: - Developing a computational Artificial Intelligence form finding design framework to shape
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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neuroimaging methods to investigate the cognitive and neural mechanisms of episodic memory and how they change in healthy and pathological aging. Our lab investigates cognitive and neural mechanisms of memory
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policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
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prototype fishing systems that integrate detection and startling mechanisms with minimal seabed disturbance. Construction and experimental testing will be supported by a team of electrical and mechanical
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existing arsenal of systemic therapies. The post is to support a PCUK-funded project investigating mechanisms of the abscopal effect in prostate cancer – the effect that treating the primary tumour may
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
, present at scientific conferences, and contribute to collaborative proposals. Minimum Education and Experience Requirements Ph.D. in Oceanography, Fluids Dynamics, Mechanical Engineering, Applied
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-capacitive devices and magnetoelastic sensors, that can be integrated into implants to monitor mechanical forces, strain, and physiological changes in real time. These “smart implants” are designed not only