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areas for development, implementation, and evaluation of (1) advanced FDD and control tools (including both model predictive control (MPC) and machine-learning) for building HVAC and district energy
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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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Responsibilities as needed: Plan and conduct research to develop machine learning techniques for the tuning and performance optimization of ECR ion sources. Contribute to VENUS's overall software development
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research on topics related to machine learning, data analytics, and thermal resilience modeling. You will also support maintenance of building energy software tools such as OpenStudio measures, CBES, and
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for the group and the division. May supervise metrology laboratory staff. What is Required: PhD or equivalent in years of relevant work experience in relevant scientific or engineering disciplines, as
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division. May supervise metrology laboratory staff. What is Required: PhD or equivalent in years of relevant work experience in relevant scientific or engineering disciplines, as demonstrated by a broad
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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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for development, implementation, and evaluation of (1) advanced control tools (including both model predictive control (MPC) and machine-learning) for building HVAC and district energy systems, and (2) heat pump
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in electrochemistry research. What is Required: PhD in chemical engineering, mechanical engineering, or related field. Experience in conducting and interpreting electrochemical techniques. Excellent
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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