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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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characterize the spatio-temporal contexts that favor crises. • Development of advanced predictive models (multivariate approaches, machine learning) combining event data, snow and weather data, and remote
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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, statistics, or mathematics OR a strong background in gene engineering and functional interrogation of hematopoietic stem and progenitor cells. Strong knowledge in bioinformatics, machine learning, statistics
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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2
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National University of Science and Technology POLITEHNICA Bucharest, Pitesti Branch | Romania | 23 days ago
(machine learning, deep learning); adaptive control and algorithmic optimization; integration of AI models in embedded systems and software platforms. APPLICATION Before applying, all candidates are invited
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://www.academictransfer.com/en/jobs/357341/postdoc-position-on-federatedco… Requirements Specific Requirements We are looking for a researcher who sits at the intersection of Pervasive/Mobile Computing and Machine Learning
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the medium and long term. We are looking for a Machine Learning Research Engineer: The ideal candidate will bring deep expertise in state-of-the-art deep learning methods applied to computer vision, 3D
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advising models and proactive, inclusive pedagogy. Experience in fostering collaboration and providing guidance to academic advising teams. Skills and Knowledge: Deep understanding of academic advising
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of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation of the mathematical models of the patho-physiology and PK/PD