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Field
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Location ESRIN, Frascati, Italy Description Data Quality and Cal/Val Manager for Atmospheric Sensor Missions in the Sensor Performance, Products and Algorithms Section, Earth Observation Mission
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networks, transformers, and diffusion models. Proven experience building AI solutions using classical ML algorithms such as decision trees, gradient boosting machines, and shallow neural networks
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networks, online analysis with delay, and theory of distributed algorithms. Job description In our group, we try to apply and unite the approaches and techniques of theory and practice. Some members of our
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new algorithms to analyse compliance of CER according to relevant Australian standards (AS 4777.2020.2, CSIP-AUS, IEEE). Creating new algorithms to analyse curtailment of CER according to relevant
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that develops advanced AI compute solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid hardware architectures
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developed: Write and maintain code to implement the core functionality and system logic that powers the application. Design algorithms and procedures for negotiating agreements between transport companies
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for the acquisition and storage of radiofrequency data. Develop (train and validate) AI and ML algorithms to detect and mitigate RFIs. Implement other RFI detection and mitigation algorithms (pulse blanking
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the values are drawn independently from known distributions. These results have been widely applied in areas such as auction theory, resource allocation, and stochastic optimization. The interdependent value
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methods that can adapt to changing external conditions and continuously learn from data in a distributed way. Coupling of new theory with effective implementation strategies have the potential to make a
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algorithms Improve performance through tuning the GPU code Document, test, and debug revisions of the software for release Coordinate conversion of LM states of cells into coarse-grained atomistic