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Field
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-Doctoral Fellowship (R$ 12,570.00/month) + Technical Reserve equivalent to 10% of the annual value of the fellowship to research-related expenses; • Initial duration of 24 months, renewable. Location: School
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) in Piracicaba. This opportunity is open to candidates of any nationality. The selected candidate will receive a FAPESP Post-Doctoral fellowship in the amount of R$ 12,570.00 monthly and a research
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-1vQAcMl8fsq_JdC3Psfily4yeZBiZOexayaPVAhXNXyuoPz1kS7GIgyLSKqlf1ayWjkHNMBDJZ4lp_bb/pub . The fellowship lasts 24 months and is open to Brazilian and international candidates. The selected candidate will receive a FAPESP Post-Doctoral fellowship in the amount of R$ 12,570.00
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/2025. The opportunity is open to Brazilians and foreigners. The selected candidate will receive a FAPESP Post-Doctoral Scholarship of R$ 12,570.00 per month, along with a Technical Reserve equivalent to
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collaborative work. Skills with computational tools for analyzing biological processes are desirable. The scholarship is worth R$ 12,570.00 monthly and includes a technical reserve of 10% of the annual
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. Letter of recommendation from PhD advisor. Conditions: Monthly fellowship: R$ 12,570.00; Technical Reserve: 10% of annual amount (research-related expenses); Open to Brazilian and international candidates
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the amount of R$ 12,570.00 monthly and a research contingency fund, equivalent to 10% of the annual value of the fellowship which should be spent on items directly related to the research activity. More
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Post-Doctoral fellowship in the amount of R$ 12,570.00 monthly and a research contingency fund, equivalent to 10% of the annual value of the fellowship which should be spent on items directly related to
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."The fellowship offers a monthly stipend of R$ 12,000.00 for an initial period of 12 months, with the possibility of renewal for an additional 4 months. A 10% technical reserve is also provided. The position
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets