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research in navigable audio reproduction, acoustic sensing AND acoustic signal processing. Where to apply E-mail efren.fernandez@upm.es Requirements Research FieldPhysics » OtherEducation LevelPhD
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processing. The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from investigating fundamental properties
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Doctoral Researcher in statistical signal processing. The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from
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analysis and visualization, signal processing, and ideally machine learning. • Working knowledge of Distributed Acoustic Sensing (DAS) and its applications in seismology (appreciated). • Aptitude
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Chaire d'Excellence-funded project “Nonstationary Models of Biological Signals” (NOMOS), Principal Investigator Prof. Anna Dudek. According to the requirements of this funding program, candidates should
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Inria, the French national research institute for the digital sciences | Bures sur Yvette, le de France | France | 20 days ago
physiological and neural recordings (EEG, fNIRS, ECG, blood pressure, and PPG) with advanced signal processing, mathematical modeling, and artificial intelligence. This project aims to provide new insights
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Nonstationary signals are at the forefront of modern statistical analysis, as many observed phenomena cannot be adequately modeled by stationary processes. The NOMOS project aims to develop a new generation of
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: Strong background in communication theory, signal processing, and wireless communications Proven track record of publications in relevant IEEE journals and conferences Extensive experience in physical
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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Limitation:Temporary (2 years) Contract:TV-L Your tasks Develop and implement computational pipelines for processing and analyzing ONT RNA/cDNA sequencing data. Apply machine learning and signal processing approaches