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spectral analysis, entropy-based metrics, graph representations of cardiac conduction, and supervised, unsupervised, and deep learning approaches for classification of abnormal electrical activity within
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to apply Website https://www.academictransfer.com/en/jobs/363316/11-phd-positions-in-the-excelle… Requirements Specific Requirements An outstanding, motivated, enthusiastic, curiosity-driven researcher. Deep
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Job description We invite applications for a fully funded PhD position in the area of Scientific Machine Learning (SciML), which integrates data-driven machine learning techniques with established
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This is a part-time fixed term position -- 20 hours per week, with an anticipated duration of 6 months. Join a dynamic team of motivated individuals with deep collective experience throughout
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/Qualifications Skills in acoustics and audio. Prefereably skills in machine learning and deep learning. Specific Requirements Education in acoustics. Knowledge of acoustical measurement techniques, as
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decision-making, computational efficiency, generalization under changing market conditions, and safe constraint handling. The PhD candidate will develop and validate decision-support methods based on deep
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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resources efficiently. In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will
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such as mechanistic, chemometric, deep learning, and physics-aware models. Improve robustness and reliability of the developed methods for deploying AI models in real environments utilizing augmentation
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of cryptographic implementations and hardware-security countermeasures. Experience with hardware reverse engineering, debugging interfaces, or firmware analysis. Experience with machine learning, deep learning