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–5): selection of relevant climatic variables and application of statistical modelling and/or machine learning techniques to predict risk. 3) Preliminary validation of the predictive model using
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1 Apr 2026 Job Information Organisation/Company Faculty of Sciences of the University of Porto Research Field Biological sciences » Other Researcher Profile First Stage Researcher (R1) Positions
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of Computing and Information Systems. Benefits This prize provides a one-off payment of $5000. Amount: Up to $5,000 Duration: One-off Quantity: At least 1 Eligibility and selection criteria Eligibility To be
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Engineering or Industrial Engineering and Management) - 10 points; Others Masters – 2 points) b) Experience in applying machine learning algorithms, data preparation, normalization, feature selection, and
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for spectral and spatial data pre-processing, as well as on machine learning algorithms, chemical map reconstruction, and algorithmic correction of galvanometric scanning.; Training will cover Python programming
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Acquisition Systems, Automation, Data Science and Machine Learning applied to Advanced Data Acquisition Systems, as well as computational learning techniques, with application in the context of manufacturing
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Recipients profile/category Mandatory requirements: Bachelor’s degree in computer engineering. Enrolment in a master programme in Computer Engineering. The documents proving the enrolment in a master programme
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for this grant: Requirement 1: - Be a student enrolled in a doctoral program in the area of Materials science, Machine Learning computational science, Coating and surface engineering a requirement to be duly
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Instituto Superior de Contabilidade e Administração do Porto do Politécnico do Porto | Portugal | about 2 months ago
23 Feb 2026 Job Information Organisation/Company Instituto Superior de Contabilidade e Administração do Porto do Politécnico do Porto Department Divisão de Gestão de Pessoas Research Field Cultural
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application of statistical Machine Learning tools. WORK PLAN Collaborate in the following tasks of the project: a) Contribute to the design and development of the Life Cycle Assessment (LCA) system; b) Support