84 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" positions in Brazil
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digital collections; references to up to five recent publications and/or presentations (last three years) demonstrating expertise in the relevant topics. See more: https://www.acervosdigitais.fau.usp.br
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% of the annual value of the fellowship which should be spent on items directly related to the research activity. Where to apply Website http://www.fapesp.br/oportunidades/9299 Requirements Additional Information
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the research activity. Where to apply Website http://www.fapesp.br/oportunidades/9294 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility
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the research activity. Where to apply Website http://www.fapesp.br/oportunidades/9303 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility
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requirements: Background in water resources management, water, and public health. How to apply: Send to nardocci@usp.br : 1) CV, 2) letter of interest, 3) letter of recommendation. Where to apply Website http
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publications abd advanced English proficiency. Experience in student supervision is desirable. Candidates must also meet the eligibility criteria for FAPESP post-doctoral fellowships (see https://fapesp.br/en
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and Supply (SAASP). Duration: 36 months (full-time) Expected start: April 2026 (flexible) How to apply Applications should be submitted only through the Google Form: https://docs.google.com/forms/d/e
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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fellowship is at: fapesp.br/oportunidades/9189 . Where to apply Website http://www.fapesp.br/oportunidades/9189 Requirements Additional Information Eligibility criteria Eligible destination country/ies
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learning-based segmentation, multimodal image fusion, and radiomic feature extraction to construct clinically relevant prognostic models. Conducted at the Heart Institute (InCor) of Hospital das Clínicas