10 machining-"https:"-"https:"-"https:"-"https:" research jobs at University of California
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The Applied Mathematics and Computational Research Division at Lawrence Berkeley National Laboratory (Berkeley Lab) is seeking a Postdoctoral Researcher – Scientific Machine Learning & Computational
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Lawrence Berkeley National Laboratory is hiring a Postdoctoral Researcher – Machine Learning for Materials Science within the Molecular Foundry division. Molecular Foundry is a Department of Energy
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science, machine learning, AI, or any computational science discipline of interest to the Computing Sciences Area and Berkeley Lab. Fellows apply advances in these fields to computational modeling
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absence of large-scale, systematically generated functional measurements needed to adapt, evaluate, and validate these models. You will have the opportunity to work at the intersection of AI, machine
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the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a
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petition that would require payment of the $100,000 supplemental fee. This position is covered by the collective bargaining agreement between UAW (United Auto Workers) and the University of California
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mentorship. Develop, implement, train, and validate machine learning and deep learning models for AI-driven prediction of cell physiology, metabolism, and functional behavior, with input from the research team
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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic
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and computer-based data management systems Experience maintaining organized and accurate records Excellent interpersonal and communication skills, including the ability to interact professionally with
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to further our understanding of Earth system processes and to enable environmental management. This includes working with ESS-DIVE users and the broader community to create machine-readable data products and