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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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requirements: PhD obtained less than seven years ago in Chemistry, Materials Science/Engineering, Chemical or Biomedical Engineering, Biotechnology, or a related field. Proven experience in electroanalysis and
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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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, statistical analyses (including multivariate approaches), and scientific writing. Mandatory requirements: PhD in physiology, ecology, neuroendocrinology, molecular biology, or related fields. Strong experience
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, public land management, or urban and housing regulation. They must hold a PhD awarded within the past seven years, have an outstanding graduate academic record, be available for full-time, on-site research
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preparation, as well as writing scientific papers and reports. Mandatory requirements: PhD completed in the fields of agricultural or biological sciences; practical experience in artificial intelligence
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feed, in collaboration with the multidisciplinary team of the Thematic Project funded by FAPESP through grant number 2021/08152-0 . Mandatory requirements: PhD obtained within the past 7 years in
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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