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digital signal and image processing, IoT, cyber security, deep learning, and software systems. Applications in healthcare, multimedia, and sustainable urban environments are encouraged. School
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=26749 PhD position in biomedical research (m/w/d) Stellenanzeige merken Stellenanzeige teilen wanted
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 7 hours ago
characterization of these devices as well as proof-of-concept prototype electronics that will be manufactured in more traditional solid-state processes. As part of this project, you will be expected to work closely
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techniques for modelling and monitoring the infusion and curing process and this PhD will bring these elements together to form a digital twin of the process. This digital twin will be used to predict
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focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head
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methodology to generate confidence in such decision, potentially reducing maintenance costs and down-time for offshore wind energy production. The images taken by each drone are loaded into the pre-processing
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crystalline rocks) using 4D µCT imaging Establishing the role of deformation in particle remobilisation and preferential flow path creation that controls clogging patterns Developing predictive digital rock
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proposal. This PhD will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation on heavily-littered coastlines, in partnership with community groups
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the research groups active at the KU Leuven Ghent Campus. This funding call is open to all EU and International applicants. Keywords: Digital Image Correlation, Experimental and Computational Mechanics
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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing