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Areas (Codes 25–29) 1. Machine Learning (Code 25) Objectives: Support UFABC’s undergraduate and graduate programs, strengthen research in Machine Learning, and expand English-taught course offerings
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. The project aims to validate and standardize use of advanced, minimally invasive imaging modalities as complementary tools to conventional necropsy for diagnosing lesions and determining causes of death
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models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue samples. Requirements: PhD completed by
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Professor will primarily, though not exclusively, teach courses related to the subfields defined in the selection process. Regarding the interdisciplinary programs, the professor should support various
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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