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, Sputtering or MOCVD systems for microelectronics and emerging sensor technologies. Key Responsibilities: Develop and optimize wafer-scale 2D materials, including TMDCs, MXenes, and MOFs, for microelectronics
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) or discrete manufacturing (e.g., electronics assembly, automotive, home appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault self
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molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental protocols and equipment. · Design, execute and document experiments with sufficient detail to understand
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. Working closely with partners in the IMPRESS project, you will analyse their materials and provide valuable insights to help optimize device performance. Additionally, you will support collaborators by
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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refinement of innovative research methodologies and will independently design, optimize, and execute complex immunologic and molecular experiments across in vitro, ex vivo, and in vivo model systems. Technical
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of neuronal and vascular responses; Contribute to the instrumental optimization of the imaging system (detector configuration, illumination control, multi-camera synchronization); Analyze and interpret
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and
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of the experimental approach will include: Bayesian reconstruction of events on billion-year timescales, determination of optimal embeddings and encodings for protein structures, multiple structural alignments
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of uncultured viruses. The research for this position aims to extend this approach to identify optimal assembly conditions for viral capsid assembly fromuncultured viruses. This requires integrating AI-based