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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 11 hours ago
bulk LWIR materials, and further work is needed to fully exploit this approach for high QE and low noise in large LWIR arrays. Significant enhancement is also possible in the design and fabrication
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, talking or hearing. No special vision requirements. Work Environment: Lab environment; moderate noise. Posting Number: 25ST2665 Create a Job Match for Similar Jobs About Rutgers University Rutgers
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vibrational spectroscopy (Dr Andras Gorzsas, Science for Life Laboratory (SciLifeLab) group leader, https://www.umu.se/en/staff/andras-gorzsas/ ). Project description The research project concerns method
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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-noise interferometer to measure the gravitational phase shift of a single photon across a two-meter height difference. Responsibilities will include carrying out original research, mentoring students
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structural topology optimization vision-based structural health monitoring autonomous and drone-based infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil
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Physical Demands: Standing, sitting, walking, talking or hearing. No special vision requirements. Work Environment: Lab environment with moderate noise. Radioactivity and hazardous chemicals are used in
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Appointment Term: Two years Appointment Start Date: Around end of summer 2025 Group or Departmental Website: https://digonnetgroup.stanford.edu/ (link is external) How to Submit Application Materials: silurian
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the ability of LLMs to identify narrative similarities in historical documents, despite noise, linguistic variations, and narrative complexity. Evaluate the performance of LLMs and adapt learning to better