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Field
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closely with signal processing pipelines built on real measurement data — including baseband I/Q signals — and contribute to both algorithm development and experimental validation. The role involves close
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Systems Analysis and Synthesis https://www.cs.aau.dk/research/research-groups/quantum-systems-analysis-and-synthesis-qsas The Department of Computer Science features a broad range of synergistic activities
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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unsupervised techniques, time-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple
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postdoctoral research project. The project focuses on the development and application of a remote sensing algorithm for monitoring the physicochemical properties of aerosols based on optical measurements taken
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this postdoc position, the focus is on methods and algorithms for large-scale graph analytics, in particular network science approaches for analyzing longitudinal, population-scale relational data derived from
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models were successfully developed with methods of Quantum Machine Learning. In cooperation with the University partners the aim of this project ls to translate classical analysis and simulation algorithms
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will develop an approach
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of novel robotic architectures, with the ultimate goal of developing an original technology with no international equivalent and strong prospects for industrial and clinical applications. Project Overview
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities