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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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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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demonstrated experience. Additional Responsibilities as needed: Plan and conduct research to develop machine learning techniques for the tuning and performance optimization of ECR ion sources. Contribute
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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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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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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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Knowledge in machine learning. Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/ Career Requested Application Materials: Curriculum Vitae
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, Chemistry, or other related field. Pump-probe experimentation. Basic knowledge in machine learning. Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https
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or combine laser, mass spectrometer or optical spectrometer components as needed. Apply computer analysis and simulation programs to interpret experimental data and characterize material surfaces. Carry out