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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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at one of OCP Group’s production sites. The project will rely on Operations Research and Machine Learning approaches. The objective is to redesign the extraction methods by considering their impact on
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empirical expertise in the complex social dimensions of climate extremes, focusing on coastal and inland regions experiencing ecological and land loss. The successful candidate will demonstrate deep knowledge
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on memory enhancement through deep brain stimulation (DBS), virtual reality applications, and trauma therapy in neuroscience. Key Responsibilities: · Design, execute, and analyze complex experiments and
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motivated, experienced working with animals, and have a deep understanding of immunology and immunological characterization techniques. The candidate should also have strong written and oral
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
partners in LMICs; deep understanding of and/or experience working in informal settlements; community-based work; willingness and ability to travel overseas; record of writing and winning grants; and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 3 hours ago
biogeochemical model using times series forecasting and machine learning. The Post Doc will focus on one or two of the questions depending on their expertise and interest. Minimum Acceptable Education & Experience
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Postdoctoral Affairs to learn more about our postdoctoral community. Resume/CV and cover letter should be included with the online application. Stony Brook University is committed to excellence in diversity and
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lagoon and surrounding off-shore region. The project will also engage closely with Stanford Robotics to develop approaches for assessing deep water wrecks, supporting the development of the next generation
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to new policy-relevant questions is more important than deep, preexisting experience with electricity policy. Consistent with its obligations under the law, the University will provide reasonable