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Research Fellow in Health Services Research Apply The role We are seeking a highly motivated, experienced health services researcher to work on the SIGNAL-BREAST project which aims to agree the
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doctoral candidates with strong theoretical foundations and practical expertise to drive innovation in Europe’s future telecommunications landscape. More information about ANCHOR network can be found https
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Proficiency: Excellent command of Python and fluency with the PyTorch framework for developing and adapting neural network architectures. Signal Processing: Solid understanding of signal processing, which
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demodulation techniques, and the development of signal-processing methods adapted to new sensing applications. The postdoctoral researcher will work within a multidisciplinary team combining
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Washington State University | about 1 month ago
, including centralized program origination, audio distribution, automation, and signal transport systems that support broadcast operations throughout the network. Working with a high degree of independence
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Devices, Power and High-Frequency Devices •Malware Analysis, Network Security, IoT Security, Secure Software and testing, Secure Coding, Cyber-physical Security •SoC Design (AI/ML Chips, Embedded Processor
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Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | about 1 month ago
improving performance in wired/wireless communications and advanced sensing, is pushing the integration of analog/RF/mm-wave and mixed-signal systems. In these domains, energy-efficient wideband signal
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explainable and localized detection methods for watermark and deepfake attribution, especially when generated content is mixed with other audio sources. Studying robustness against signal-processing attacks
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Your Job You will participate in an international team in an EU-funded Doctoral Network project called MINDnet. The project consists of 15 Ph.D. students at 7 universities, one research center and
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Research Unit of Health Sciences and Technology (HST), Faculty of Medicine the Center for Machine Vision and Signal Analysis (CMVS), Computer Science and Engineering, Faculty of Information Technology