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Field
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environment with expertise in product development, robotics, automation, digitalization, and biomedical technologies. The PhD will contribute directly to the development of technologies that may accelerate drug
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-inspired computing paradigm with the potential to drastically reduce energy consumption while enabling faster inference than conventional digital architectures. A major challenge, however, is the development
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PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis Job No.: 695949 Location: Clayton campus Employment Type: Full-time Duration: 3-year and 3-month fixed-term appointment
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strong asset.•Experience in the analysis of high-dimensional biological data (single-cell or spatial transcriptomics, digital pathology or biomedical imaging) is an advantage.•Comfortable working on Linux
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of next-generation targeted cancer therapies while working with world-leading imaging technologies in an international research environment? Then this fully funded PhD position at the Maastricht MultiModal
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for new and improved metrology solutions to meet these challenges. Digital holography (DH) is a technology that can provide single shot full wavefield imaging of flat single layered structures. However, its
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the operational state of buildings from acoustic and complementary sensor data. By combining multi-microphone acquisition techniques with additional sensing technologies, advanced digital signal processing and
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: Digital twin development for hydrogen-assisted crack propagation in buried steel pipelines [APS, Tata Steel; Karo Sedighiani] PhD 7: Cryogenic interface heat transfer for advanced thermal interfaces [Thermo
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
retrieval: reconstructing the original digital data from the sequenced symbols. This PhD project focuses on the first and fourth challenges, by developing joint compression and error-correction algorithms
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probabilistic digital twins of coronary arteries. The goal is to create patient-specific models that combine anatomical and hemodynamic information derived from routine clinical imaging. By providing quantitative