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models for turbulent reacting flows. Development and application of machine learning tools in one or more of these areas: chemical kinetics, turbulent combustion, and extreme event prediction. Job Family
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modeling of crystals, dislocation dynamics, and defect analysis, linking atomic-scale simulations to macroscopic properties. Familiarity or interest in machine learning methods and computing frameworks
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in soil processes, plant physiology, plant traits, and species composition Strong data analysis skills, including proficiency in R or Python coding, and/or machine learning techniques Excellent writing
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encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
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, inclusive, and accessible environment where all can thrive. Additional Preferred Qualifications: Working knowledge of power system protection and control. Familiarity with Machine Learning. Familiarity with
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their environmental impacts including energy use, water use, emissions, and resource depletion. Coursework and some project experience in application of mathematical optimization, statistics, or machine
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researchers performing molecular modeling and machine learning activities. The candidate will be expected to perform ion conductivity experiments with thin film polymer electrolytes. The candidate will use