45 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" uni jobs at Michigan State University in United States
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approaches. Through innovative work combining machine learning with new paradigms for direct solvers of high-dimensional partial differential equations, members of CHaRMNET aim to overcome this challenge
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safety; experience in the use of laboratory systems and computer software; strong communication and customer service skills; ability to work collaboratively demanding environment; multi-tasking and meeting
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[map ] Subject Areas: Mathematics, AI-based drug design and discovery, Bioinformatics/Protein Engineering/Single-cell Omics Data, Mathematical AI/Machine Learning/Deep Learning, and Computational
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expansive work experience in supervision, all areas of farm work/production with in specific animal groups and/or crops related to the area of employment; experience in computer usage; and knowledge of farm
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Internal Number: 1109662 Position Summary The executive secretary provides high level support for the assistant dean for global learning and innovation and Center for Global Learning and Innovation
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technologies including databases, web-based data systems, e-mail, spreadsheets, and word processing. Required Application Materials Resume Cover Letter Remote Work Statement MSU strives to provide a flexible
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systems; experience working on large tonnage mechanical and absorption chillers; experience with the servicing of smaller systems, including window air conditioning units, refrigerators and ice machines
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proficient in the use of a laptop computer. A lifelong learner and problem solver with strong technical skills and communication skills, who focuses on innovative solutions aligned with University goals. Equal
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[map ] Subject Areas: Mathematics; Physics; Astrophysics; High Performance Computing; Machine Learning Appl Deadline: 2025/12/16 04:59 AM UnitedKingdomTime (posted 2025/11/20 05:00 AM UnitedKingdomTime
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of freedom per dimension d. Foundational kinetic models often have N∼256 and d≥6, making direct numerical simulation intractable with traditional approaches. Through innovative work combining machine learning