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to industry and developments with Deep Learning (DL), Computer Vision (CV), Transformers, Large Language Models (LLMs), Natural Language Processing (NLP). Mandatory requirements • Bachelor's degree
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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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, and machine learning; and the development of ecological indicators for environmental monitoring in the Campos and Santos Basins, Brazil. Mandatory requirements Applications from people with training in
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Experience in plant breeding for resistance to biotic and/or abiotic stresses, programming, machine learning, and genomic data analysis. Desirable requirements 1. Cost-effectiveness assessment: rapid
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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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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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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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chromatography. The candidate will prepare samples for immunopeptidomics by liquid chromatography coupled with mass spectrometry tandem (LC-MS/MS), analyze large datasets, and develop scripts and machine learning
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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