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. Implement parallelized optimization studies on clusters and other HPC resources. What is Required: Ph.D. in Mathematics, Engineering, or Physics. Experience in two or more of the following areas: Application
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electro-mechanical background. Substantial technical understanding of mechanical or electromechanical theory and work practices, scientific and engineering principles, and technical mathematics. Substantial
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Engineering, Geoscience, Computational Science, Data Science, Applied Mathematics, Physics, Chemical Engineering, or other related fields. Demonstrated research experience and knowledge in areas of related
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developing mathematical models for building energy simulation Demonstrated strong skills in developing models in languages and simulators in the domain of building energy and control systems. Strong knowledge
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to accelerate the adoption of these technologies, along with assisting in disseminating the results with key stakeholders. You will be expected to make contributions to the creation of mathematical models and
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The Physics Division at Lawrence Berkeley National Laboratory (LBNL ) has an opening for a Cosmic Microwave Background Divisional Fellow who will make substantial contributions to the design, construction, operations and scientific analyses of the CMB-S4 project; collaborate with the scientific...
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Laser Technologies Group in LBNL"s Energy Technologies Area has an opening for a Postdoctoral Scholar to join the team. In this exciting role, you will participate in the development of Laser Induced Breakdown Spectroscopy (LIBS) and Laser Ablation Molecular Spectrometry (LAMIS) for the analysis...
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Computer Science, Applied Mathematics, Computational Science (or related fields) and a minimum of 12 years related experience and 5 years in a supervisory role. Expertise in one or more of the following areas
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developing new funding initiatives as needed. What is Required: Requires a PhD in Physical sciences (physics, chemistry and materials science), Quantum Information, Mathematics, Computer Science, Computational