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in a dynamic and internationally recognized group. Activities include generation of genetically-modified mouse models, isolation and in vitro culture of mouse germ and embryonic cells, molecular
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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(MRO), as well as interpretation of results and collaboration with CEMol teams and partner institutions. Mandatory requirements: PhD in Materials Science or related fields; proven experience in
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, microstructure, and properties. Data analysis and preparation of scientific papers, reports, and conference contributions. Mandatory requirements: PhD in Materials Engineering, Metallurgical Engineering, or
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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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, 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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architecture associated with responses to HLB, integration of “omics” data, and complementary analyses on gene family analyses, transposons, small RNAs, and microbiomics. Mandatory requirements i) Hold a PhD
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at https://www.labcidade.fau.usp.br/vaga-de-pos-doutorado/ by August 17, 2026. Required documents: FAPESP-format CV, graduate transcripts (Master's and PhD), and a cover letter (up to 1,500 words
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well as in the operation of analytical instruments for the structural characterization of nanostructures. The candidate must have a PhD in Physics, Chemistry or Materials Engineering (or related). How to apply
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findings to public-sector partners; and contributing to reports, journal articles, and national and international conferences. Mandatory requirements: PhD awarded within the past 7 years by a recognized