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, electrical engineering or simila,r with an affection for machine learning; You are an independent and original thinker with a creative mindset; You are a fast thinker with excellent analytical and
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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: Reporting to the campus department instructional leader, adjunct instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and
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maintain a professional appearance and manner Willingness to learn and interact with new unfamiliar technology Advertised Physical Requirements: Regular bending, stooping, reaching, stretching, standing
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the supervision of the PI, including proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. Pursue research topics
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skills with the ability to learn new computer skills including word processing, spreadsheets, databases, and PI archive database Exposed to heat, noise, dust, and hazardous areas around machinery
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execution and milestone completion. Job Requirements Strong background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations
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website (http://www.mouncelab.com). Experience in molecular virology is preferred but not required. Responsibilities are flexible according to discussions between the applicant and the PI.Interested