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Field
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-generation permanent magnets using a powerful combination of high-throughput computation, machine learning, rapid synthesis and efficient characterization. This position requires expertise in synthesizing and
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 2 months ago
position focused on advancing crop production and physiology through field experimentation, computation (statistics and machine learning), and process-based models. The successful candidate will have an
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 22 hours ago
research for full-stack production system that includes Python/FastAPI, MongoDB, and a TypeScript/React client; (2) apply AI and machine learning to a challenging real-world problem; (3) gain knowledge
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Group invites applications for a Postdoctoral Fellow position. The research will develop and utilize emerging machine learning tools to remove bottlenecks in many-body simulations. Responsibilities: 1
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computer engineering degrees with previous experience in natural language processing; or computational linguistics/language technologies degrees; (b) strong programming skills and machine learning experience
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intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and scientific applications. About the research project You will work in Julian Togelius' new research
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Do you want to combine high-throughput directed evolution with machine-learning analysis of deep sequencing data to engineer better antibodies? The Sormanni Lab in the Department of Chemical
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machine learning within the scope of ACAG. The postdoc will have various opportunities for professional development, including contributing to and leading grant proposal development (e.g., external
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partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across the two teams. The position offers a strong publication trajectory at leading HCI venues
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy