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for scientific and security applications; (ii) ML model optimization for inference speed and deployment for real-time analysis; and (iii) AI model training for analog in-memory computing. The position provides
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-coherent-flux scattering by employing cutting-edge optical design and modeling, sub-nanometer-level metrology, and diffraction-limited X-ray mirror fabrication techniques. With considerable latitude
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out R&D programs focused on Electro-Photonics, Quantum Information Science, Artificial Intelligence & Machine Learning, and Neuromorphic Processing that require ASICs with specific layouts
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these applications to inform new foundational ML and NLP innovations. This work involves the development and applications of encoding and generative NLP models (e.g. large language models, LLMs), and includes model
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novel genetic pathways regulating local and systemic acquired resistance, as well as growth-defense trade-offs. Using bacterial, fungal, and viral disease models, the research will focus on identifying
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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and
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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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by publication record). Excellent programming and computer science skills. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel ML and NLP algorithms and models and
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concept through computer aided analysis, detailed 3D modeling and design, and system interface efforts. Deliver all phases of the project work – design, engineering analysis, R&D, procurement and