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, machine/deep learning (Pandas, SHAP , TensorFlow, etc.) and specific to image analysis, statistics, simulation, cloud environments (Kubernetes type, Docker-compose, virtualization, etc.), 3D environments
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others. The candidate will be working in a very multidisciplinary project that covers topics such as chemical synthesis and functionalization, materials science, characterization techniques and prototype
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for public policies that promote healthy and sustainable eating across Europe. Responsibilities Create audiovisual materials for the Planet project and the Health Sciences Studies, including recording, image
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Doctoral candidate in the nexus between doping and thermal conductivity in EU Training Network FADOS
of doping level. The Doctoral candidate will be in charge of developing imaging tools to characterize doping landscapes (via Raman) and thermal conductivity landscapes (via thermoreflectance tools
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groups and cross-disciplinary projects. It will combine technological capabilities in omics analysis, medical imaging, multi-scalar integration and AI, aiming at clinical application and the use of real
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/2) and dramatically larger physical apertures than today’s 5G MIMO systems. We call this new paradigm UltraMIMO (U-MIMO). This thesis will develop superdirective hybrid analog–digital UMIMO arrays
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operational reliability of all electron microscopy equipment. Contributing to the development of new imaging protocols and methodologies, while identifying opportunities to expand the applications of electron
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, Drug Delivery, AI-driven Drug Discovery Molecularly Targeted Drugs, Biopharmaceuticals (e.g., nucleic acid, cell-based, and protein-based drugs) Bioinformatics, Omics Analysis, Molecular Imaging
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in optoelectronics, imaging, sensing and renewable energies. We take advances in nanoscience and we transform them into nanotechnology for solving real-world problems that current technology cannot
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dedicated to digital transformation in healthcare, sports, food, and environmental monitoring through advanced (bio)chemical sensing, combining electrochemistry and imaging technologies. Led by Prof. María