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biogenic particles; the effects of fronts, eddies, upwelling, and other mesoscale processes on biological communities; applications of remote sensing integrated with in situ observations, numerical modeling
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cities and databases. Mandatory requirements: PhD in engineering, data science and computing, mathematics, or statistics; experience in engineering, data science and computing, mathematics, or statistics
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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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, supported by Large Language Models (LLMs). Mandatory requirements: The candidate must hold a Ph.D. in Computer Science or a closely related field. Desirable requirements: Experience in Information Retrieval
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email ([email protected] ), an updated Curricular Summary in the FAPESP model , a motivation letter explaining their suitability and alignment with the project “Forensic discrimination of Brazilian
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mouse models, cell culture, molecular biology, processing of biological samples for omics analyses, and assessment of in vivo lipogenesis using radioisotopes. Mandatory requirements: Degree in Biological
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position within a Research Infrastructure? No Offer Description Activities and context: The Department of Natural Sciences, Mathematics and Education at the Center of Agricultural Sciences of the Federal
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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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; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets
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modeling) to design consensus COBRA antigens against avian vírus H5N1; - The post-doctoral researcher will construct hypervesiculating bacterial strains using Lambda-Red recombinase and optimize OMV