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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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for 3 years. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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Models, Knowledge Graphs, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the following areas: Natural Language Processing, Knowledge Graphs, Machine
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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skilled in object-oriented coding (preferably Python) and data analysis; affinity with machine learning and explainable AI techniques, preferably in a geoscience context; good social skills. As a university
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: Computational Linguistics, Language Acquisition, Cognitive Modeling, Machine Learning The Department of Linguistics at the University of Michigan invites applications for a one-year Postdoctoral Research Fellow
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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statistical physics, control theory, and where appropriate, machine learning and data-driven techniques. The position offers a structured career development path within an active and ambitious research group