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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15
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) Limited until: 30.04.2032 Reference no.: 5022 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate
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calculations, sample size determinations and statistical analysis plan. 3. Apply machine learning approaches to integrate diverse datasets collected from study participants to identify subtle differences
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 8 hours ago
, graduate students, and recent graduates to learn about policy analysis projects across various focus areas. These areas include Domestic Energy Policy, Power Sector, Critical Minerals and Materials
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modeling. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr Fang Luo in the Department of Electrical and Computer Engineering . The incumbent will conduct
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learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in the administration of both its employment and educational policies. Duke
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opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our
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, quantum cryptography, quantum program verification, quantum machine learning, etc. ● Within the predetermined research scope and methodology, conduct research experiments in the field of Quantum
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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TAMU. Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment. Knowledge of characteristics associated with mild cognitive