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Field
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– and how can we extract it reliably? We are looking for a curious and persistent PhD student (f/m/d) who wants to discover new biological and medical insights from cutting-edge imaging and sensing
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assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and quantitative security assessment
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-assisted soft-mist inhaler for patients who cannot reliably use conventional inhalers because of weak or irregular breathing. Many inhalers depend on the patient generating sufficient inspiratory flow and
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) into reliable and efficient decisions. The work spans theory to lightweight on-hardware prototypes, with publications targeted at leading IEEE venues in communications and signal processing, and relevant AI
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-IMPACT ( TURBOmachinery Innovative Manufacturing, Processing, Analysis, Characterization, and Topology; Website: https://cordis.europa.eu/project/id/101311350 ). The TURBO-IMPACT project, funded by
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control applications? In this PhD project, you will develop methods for the analysis, verification, and design of neural-network-based controllers. Rather than treating safety and stability as properties
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and statistical methods as part of a close collaboration between Uppsala University, Westinghouse, and Vattenfall? Would you like to contribute to the development of fast, robust and reliable
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matter in non-equilibrium conditions, defining new observables, and applying data-driven analysis to distinguish coherent response from fluctuations, correlations and phase-transition dynamics. Main tasks
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data analysis would be highly advantageous but is not essential. We value reliability, care in laboratory practice and willingness to learn as much as formal experience. Excellent communication and
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results, numerical modelling, and analytical approaches to support the development of respective reliable and efficient design concepts. Led by Prof. Christoph Odenbreit, the ArcelorMittal Chair of Steel