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devices and microsensors, heterogeneous integration/3D packaging, and other broad areas of semiconductor/microelectronics. Responsibilities: Nanofabrication in the cleanroom and characterization/measurement
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 4 hours ago
to artificial intelligence and machine learning, quantum information and sensing technologies, high-performance computing, communications technologies, semiconductors and microelectronics, biotechnology
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backgrounds to join our community. The Department of Electronics and Nanoengineering conducts research and arranges related courses in the fields of microelectronics, micro and nanotechnology, radio engineering
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. Requirements: A PhD degree related to organic optoelectronics or other closely related fields such as microelectronics/applied physics; Proven experience in vacuum thin-film deposition, solution thin film
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. Our lab works in the areas of ultrafast science, nanoscale thermal transport, and microelectronics, for applications in energy-efficient computing, thermal management, and energy conversion. We seek
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such as microelectronics and self-assembly of nanocomposites. Therefore, we seek highly motivated candidates to drive the project independently while interacting closely with senior members of the research
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-slope transistors for energy-efficient microelectronics applications as a part of a DOE Microelectronics Science and Research Center (MSRC) project. You will explore the materials and device physics of 2D
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Associate to conduct novel research investigating 2D material heterostructures for developing steep-slope transistors for energy-efficient microelectronics applications as a part of a DOE Microelectronics
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techniques to control the growth environment and material consistency across the wafer targeting applications in microelectronics and quantum information science. This position resides in the Functional Hybrid
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security, artificial intelligence, image and text processing, microelectronics, etc. The laboratory is particularly involved in AI research, notably developing work on generative models to accelerate