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. Experience with developing machine-learning surrogates for structure-property relationship, generative AI models, material representations, machine learning force-fields (especially extensions to spinful
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or PhD in Computer Science, Computer Engineering, Cybersecurity. Experience architecting and implementing complex distributed systems and willingness to learn Experience in cluster computing and scaling
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or PhD in Computer Science, Computer Engineering, Cybersecurity, or related fields with 2 years of experience. Experience architecting and implementing complex distributed systems and willingness to learn
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, using a questioning attitude, considering hazards for every task,and never stop learning. Align behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and
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, completeness, and adherence to internal and external standards The ability to learn quickly and adapt to change is necessary. The candidate is expected to be able to work in a team environment as well as perform
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. Proactive mentality with a commitment to continuous learning and improvement in the rapidly evolving HPC field. Special Requirements: Visa sponsorship: Visa sponsorship is not available for this position
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant
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ability to acquire new knowledge and learn new skills. Demonstrated interpersonal, verbal and written communication skills. Ability to develop plans to address complex problems, be proactive, work
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budgeting, tracking, forecasting. Capable of advanced Excel and SAP queries. Training and/or certification in project management. Ability to learn new software skills effectively (PowerBI, RESolution