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Field
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, and evaluation The ideal candidate will lead their own project, and also collaborate with and support 1-2 PhD students on their projects. The ideal candidate will also be interested in learning
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along with experience in applying Artificial Intelligence (AI)/Machine Learning tools, OR a PhD in AI/Machine Learning with experience in plasma physics or other strongly coupled physical systems
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, operation, control, and security. Required Knowledge, Skills, and Abilities: A PhD. with a broad knowledge of electric power systems. Demonstrated background in artificial intelligence (AI)/machine learning
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Physics, Electrical Engineering, Material Science or closely related field in hand
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NASA LAS director. Candidates must have a PhD in a related field. Four years professional experience in machine learning is preferred. FAA Part 107 and/or Part 61 piloting certifications are encouraged
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experiences that developed or applied at least one of the following techniques to solve a problem related to the broad application areas as listed above: signal processing/time series analysis, machine learning
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networks, brain functions, or molecular shapes. For more information, contact [email protected] . Position Requirements PhD in Computational Neuroscience, Machine Learning, Computer Science, Physics
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equipment for biomass conversion. • Experience with modeling and machine learning. . Job Application Submission Window The anticipated closing window for application submission is up to 30 days and may be
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record, and available funding. Education Requirement: A PhD degree (or about to complete) in machine learning, or a closely related field, is required. Required Qualifications: Practical experience in
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have their entire salaries covered by external funds. Candidates must have a PhD degree or equivalent and a minimum of 4 years of postdoctoral training. Expertise in bioinformatics/ transcriptomics