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advanced correlative microscopy techniques, combining coherent X-ray diffraction imaging (CXDI) and STED super-resolution microscopy. The researcher will: • Develop new multimodal imaging strategies; • Work
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: Experience with electrochemical techniques applied to the characterization of interfaces and charge-transfer processes; nanostructured materials and thin films; surface functionalization and aptamer, antibody
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for general image classification tasks. We are particularly interested in applications involving weather radar imagery and medical imaging. Mandatory requirements: Ph.D. in Computer Science, Mathematics
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computing, obtained within a maximum of 7 years; application of machine learning and deep learning methods to remote sensing images; proficiency in programming (R, Python, or similar); ability to work
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transmission electron microscopy (TEM/STEM) and/or advanced image-processing techniques; proficiency in programming and in the application and development of software and computational tools for scientific data
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experience in image-based phenotyping, artificial intelligence applied to grapevine breeding, genome-wide association studies (GWAS), genomic selection (GS), and statistical analysis. Mandatory requirements
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involving geological risk management, conducting field surveys in remote areas, advanced use of ArcGIS geoprocessing tools, drone image acquisition and processing, and organizing technical events or meetings