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and radar remote sensing, climate time series, and hydrological models. The work will employ machine learning and explainable AI techniques to improve flood prediction under different hydroclimatic
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the supervision of Prof. Dr. Marilene Proença Rebello de Souza, within the project Center for Science for the Development of Basic Education: Learning and School Coexistence (CCDEB) (FAPESP Process 2024/01122-7
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the supervision of Prof. Dr. Marilene Proença Rebello de Souza, within the project “Center for Science for the Development of Basic Education: Learning and School Coexistence (CCDEB)” (FAPESP Process 2024/01122-7
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, behavioral testing, molecular biology, immunohistochemistry, confocal microscopy, and image analysis. Fluency in English and strong scientific writing skills are essential. The fellowship offers a monthly
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(HR+/HER2-) and aims to develop predictive models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue
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knowledge on signal processing, statistical analysis and computer programming skills. Deadline: 10/31/2025 Furthermore, applicants must send the following documents via email to Alberto Luiz Serpa at alserpa
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must hold a PhD in astronomy/astrophysics (awarded within the last 7 years), with experience in stellar astrophysics, survey data analysis, or machine learning, and strong programming skills
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staff position within a Research Infrastructure? No Offer Description The School of Electrical and Computer Engineering (FEEC) and the Agricultural Engineering School (FEAGRI), both from the State
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travel, computer equipment and research expenses (https://fapesp.br/en/5427 ). Applicants should submit a CV, publication list, and a concise statement detailing research accomplishments and interests
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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