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signal and/or image processing. - Skills in modeling tools and time–frequency representations. - Practical skills in scientific programming, ideally in Matlab and/or Python. - Knowledge
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The LEPMI (Laboratory of Electrochemistry and
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
respecting the specific constraints of emergency situations. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted
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, including Titan Krios and Glacios microscopes, a fully equipped crystallography platform, advanced computing clusters, proteomics and BSL-2/3 imaging facilities. The institute provides numerous training
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emerging nano X-ray imaging technologies with complementary integrative structural biology approaches for molecular mechanistic studies. Research environment The EMBL Grenoble Unit pursues an ambitious and
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Imaging applications. The laboratory is located at the interface of Engineering Sciences and Biological Sciences. The laboratory has developed numerous interactions with research teams specialized in
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simulation tools and machine learning techniques. Initially, the work will be based on the design of a database of medical images, which will be processed using convolutional neural networks to identify design
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variations or periodic signatures in radio emissions. • Application of our method to the analysis of the second half of the LoTSS-wide data, recently pre-processed (synthesis of images and dynamic spectra
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description A fixed-term research
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, https://hal.science/hal-04930868 . [2] Peyré, G., Cuturi, M., et al. (2019). Computational optimal transport: With applications to data science. Foundations and Trends in Machine Learning, 11(5-6):355–607