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developing high performance PV devices using perovskite photoactive materials. Experience of perovskite PV device analysis is essential, as is experience in the fabrication of perovskite PV devices. Experience
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XANES and XAFS. Duties: Performs experiments and analyzes data (of inorganic pollutants by natural and engineered solids) Publishes and presents research findings Supervises and trains graduate and
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university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity
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collaborative theoretical and computational research in quantum condensed matter physics Develop and implement high-performance scientific software, and simulation tools Publish research papers and present
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at the University of Munich, SAW transducers will be integrated with waveguide structures to perform spectroscopy on a small inhomogeneous ensemble (the implanted region) and to provide direct evidence of acoustic
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observation and high-resolution numerical modelling. However, the high computional cost associated with the numerical modelling approaches that we use at LIENSs (SCHISM modelling system ; Zhang et al., 2016
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
able to perform standard mammalian cell culture, including lentivirus preparation and transfections. Must be able to perform sequencing library preparation. Must be able to analyze high throughput
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://www.nocera.harvard.edu/overview). 2. Publish and present research findings in high-quality scientific journals and conferences. 3. Collaborate with faculty, researchers, and students on interdisciplinary research projects
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-management algorithms for efficient and reliable long-duration operation. Implement hardware-in-the-loop (HIL) and real-time co-simulation for validation under realistic grid scenarios. Integrate battery
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for data analysis and predictive modeling. The fellow will join a small, world-class, multi-institutional team advancing microelectronics research through AI-enhanced methodologies. You will: Perform soft X