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Berkeley Lab’s (LBNL ) Energy Geosciences Division (EGD) has an opening for a Postdoctoral Researcher in Machine Learning for Geological Carbon Storage to join the team. In this exciting role, you
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Machine Learning (ML) models and Python script or equivalent, as well as perform room temperature and cryogenic temperature electrical and mechanical measurements. What You Will Do: Perform mechanical
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group analyzing deep soil warming experiments across the world. In this exciting role, you will apply mechanistic and machine learning models to study observed effects of warming on soil and ecosystem
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and machine learning models to study observed effects of warming on soil and ecosystem carbon cycling and the mechanisms shaping the soil response, and to estimate potential soil carbon feedbacks with
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using predictive models, such as regression, classification, and other machine learning tasks Ability to independently execute tasks that require critical thinking. Demonstrated ability to write high
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tomography data. Develop new data-driven methods that leverage physics-informed machine learning for reconstructing non-rigid deformations and generative modeling of conformational heterogeneity in electron
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The Nuclear Science Division (NSD) at Lawrence Berkeley National Laboratory has an opening for a Postdoctoral Researcher, with focus on the application of machine learning techniques to address
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physics-informed machine learning (ML) for compact accelerators. Work will include operation and experiments using the High Repetition-rate Electron Scattering (HiRES) compact ultra-fast electron
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ultrafast laser systems. Experience with machine learning. Excellent verbal and written communication skills. Salary: The monthly salary range for this position is $5,374-$7,510 and is expected to start at
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, or related field, with extensive professional technical experience or additional education related to the position duties, typically minimum 2 years. Experience applying machine learning algorithms to real