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Field
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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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state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier environments. As a Postdoctoral researcher, you will
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analyzing urban data (traffic, energy consumption, environment). Strong skills in integrating IoT devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence
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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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Biology is looking for a highly motivated and independent individual to work as a Postdoctoral Associate starting August 15, 2025. This position is for a post-PhD trainee preparing for a career path as
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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successful in this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation
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, and you will join the research group led by Prof. Christa Cuchiero to work at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The research areas cover a wide range of
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-on experience with CRISPR. • Proficiency in electrophysiology, calcium imaging, and/or multielectrode arrays. • Familiarity with machine learning, imaging analysis, and/or bioinformatics. Online Application
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, concentration and functional inequalities • Mathematical aspects of machine learning and deep neural networks • Free Probability aspects of Quantum Information Theory. While excellent candidates with other