88 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" 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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required. Desired Qualifications Experience working with cleaning materials, flexible work schedules, and willingness to learn food service methods and procedures. Equal Employment Opportunity Statement All
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Hours STANDARD 8-5 Website HTTPS://RESEARCH.MSU.EDU/ Remote Work Statement MSU strives to provide a flexible work environment and this position has been designated as remote-friendly. Remote-friendly
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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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Instructions This is an in-person position with the potential for 1 remote day per week. Any questions can be directed to Jocelyn Janicek (janicekj@msu.edu ). Work Hours STANDARD 8-5 Website HTTPS
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, gender identity, national origin, citizenship, age, disability or protected veteran status. Required Application Materials Resume and Cover Letter Work Hours STANDARD 8-5 Website https
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"Hybrid", with the flexibility of regular remote work mixed with in-office work as mutually agreed upon with the supervisor. Work Hours STANDARD 8-5 Website https://finance.msu.edu/ Remote Work Statement
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upgrades and operations, while championing continuous learning, innovation, and career development for managers and staff. Note: This role requires a hybrid schedule with at least two days a week in-person
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Position Summary Michigan State University actively promotes a dynamic research and learning environment in which qualified individuals of differing perspectives, and cultural backgrounds pursue academic
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statistical approaches, including the use of AI and machine learning approaches to analyze large datasets. Demonstrate a deep understanding of and commitment to research of health disparities, including