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monthly stipend of R$ 12,570.00, for the project: “Soil carbon and functioning recovery across reforestation methods in Brazil” Host institution: ESALQ/USP – Piracicaba, São Paulo, Brazil Duration: 24
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of the main project; 2. Improve proficiency in the inverse modeling techniques provided by the PEST software, and apply them to the experimental data for calibration of the MFLUX model, as specified in the main
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to positively influence these alarming epidemiological data. The minimum requirements for the post-doctoral candidate (PD) include prior experience in platelet biology, physiology, and pathophysiology; methods
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, and analysis by using concepts and methods from machine learning, including pattern recognition, graphs, and complex networks. ** Specific Research Areas: * Develop concepts and algorithms to analyze
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graduates or students (i), and PhD candidates (ii) in Law, Social Sciences, International Relations, Economics, or related fields. ✔ Applicants from all nationalities are welcome! 💡 Preferred Qualifications
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reendothelialization assays, platelet adhesion assays, and co-culture and immunomodulation studies. They should also be willing to learn new methods as needed, such as chemiluminescence-based nitric oxide (NO) detection
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: - PhD in Business Administration, Engineering, Sociology, or Economics; - Relevant publications in the field; - Experience in qualitative and quantitative research related to ecosystems, innovation
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Physics » Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Country Brazil Application Deadline 25 Nov 2025 - 23:59 (America/Sao_Paulo) Type of Contract Temporary Job Status Full
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“Multiprofessional Center for Paralympic and Parasport Studies (CMEPP): Health, Education, High Performance, and Technology”, one of the Science Centers for Development (SCDs) supported by FAPESP. Prerequisites: • PhD
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incorporating local constraints (stress, displacement, temperature) via the Augmented Lagrangian method and global compliance constraints, applying coupled thermomechanical simulations to predict performance in