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Field
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through nearly completed). Formulate, troubleshoot and optimize research methods and techniques as needed. Independently reproduce, evaluate, research, and improve techniques currently used. Maintain
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‑guided optimizations across languages (Julia/JACC, Mojo/MLIR, Rust/LLVM). Incorporate Enzyme-based automatic differentiation and multi-language IR tooling for AI‑driven analysis. High‑Productivity
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exciting opportunity for someone who thrives in an interesting and challenging work environment. Core responsibilities include: Research in the intersection of network optimization and approximation
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and machine-learning-driven optimization frameworks for polymer composite manufacturing processes. This position resides in the Composites Innovation Group in the Manufacturing Science Division (MSD
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exciting opportunity for someone who thrives in an interesting and challenging work environment. Core responsibilities include: Research in the intersection of network optimization and approximation
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interested in pursuing an independent academic career are welcome to apply for this position. For more information: https://www.bcm.edu/people-search/ctirad-skoda-174296 Job Duties Designs, optimizes, and
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communities (SynComs) Develop and optimize co-culture and community-based assays Perform RNA extraction, purification, and characterization Apply a range of molecular and analytical techniques, including qPCR
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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Certifications/Licenses Required Knowledge, Skills, and Abilities Experience with AI-driven model updating and calibration of structural systems, including learning-based or optimization approaches Strong
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culture of resilient optimism, resourceful thinking and pragmatic dreaming that enables us to reach others every day. Visit our website to learn more about the University at Buffalo . University at Buffalo