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novel computing paradigms, providing a unique opportunity to contribute to mathematics with a clear technological impact. We are recruiting two complementary postdoctoral researchers to join this
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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significant impact on the world around us. The Department of Electrical and Computer Engineering at Carnegie Mellon University is seeking a Postdoctoral Research Associate that will contribute to cutting-edge
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, including analyzing metagenomic data (e.g., virome) and phylogenomics, statistics, and an interest in infectious disease research. The ability to develop novel computational methods using machine learning
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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significant impact on the world around us. A postdoctoral position is available in the Department of Electrical and Computer Engineering at Carnegie Mellon University (Chamanzar Lab) on Ultrasound-assisted
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spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational methods to discover unknown metabolites that have strong associations to experimental
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. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model
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processing, machine learning, computational imaging, and clinical translation. Beyond your individual research contributions, you will serve as a technical coach for the PhD researchers, helping to align