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Field
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science, machine learning, AI, or any computational science discipline of interest to the Computing Sciences Area and Berkeley Lab. Fellows apply advances in these fields to computational modeling
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including historical linguistics, semantics, pragmatics, computational linguistics, phonology, or sociolinguistics. We would like to see candidates who can communicate with and learn from both linguists and
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mentorship. Develop, implement, train, and validate machine learning and deep learning models for AI-driven prediction of cell physiology, metabolism, and functional behavior, with input from the research team
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. Programming experience in Python, Matlab, and SQL. Mathematical modeling and data analysis. Machine/Deep learning (e.g. Pytorch, TensorFlow, JAX). City of Hope employees pay is based on the following criteria
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of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical
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an industry partner. Experience with research software, data pipelines, and simulations, machine learning, high-performance computing, CANFAR, or advanced data systems. Evidence of mentoring or supervising
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) experience with non-destructive testing (NDT) methods (e.g. ultrasonic, thermography, eddy current); (c) knowledge of automation, control systems, and sensor integration; (d) familiarity with AI/machine
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 18 hours ago
tokenization, text classification, and named entity recognition. Compare traditional rule-based NLP approaches with modern machine learning-based approaches and articulate when each may be appropriate in a
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Able to adapt to change, Able to assemble, analyze and present data, Able to learn and retain information, Able to multitask, Able to plan, organize, and implement projects in a timely manner, Able to
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top-tier conferences and journals related to AI, security, privacy, digital forensics, or trustworthy computing. Solid background in Machine Learning, Digital Forensics, Security, and AI Generation