47 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at FEUP
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for 1 research grant within the framework of project “Understanding Machine Learning Systems”, financed by Faculdade de Engenharia da Universidade do Porto, under the following conditions: Scientific Area
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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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the reference BiodivNBS/0007/2023 and DOI: https://doi.org/10.54499/BiodivNBS/0007/2023 , financed by Foundation for Science and Technology, I.P , through national funds, under the European Co-financed
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the tender notice. The final decision on hiring is the responsibility of the top manager of the hiring entity. 14. Formalization of applications: 14.1. Applications must be formalized at http://www.fe.up.pt
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analysing the influence of the main machining parameters on the dynamic behaviour of cutting, with the objective of identifying instability conditions and supporting process optimization. This work plan is
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Industry, with the reference ERA-MIN3/0002/2023 with e DOI 10.54499/ERA-MIN3/0002/2023 (https://doi.org/10.54499/ERAMIN3/0002/2023 ) funded by the Fundação para a Ciência e a Tecnologia, I.P., through
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the Sustainability of Raw Materials Industry” with the reference ERA-MIN3/0002/2023 with e DOI 10.54499/ERA-MIN3/0002/2023 (https://doi.org/10.54499/ERAMIN3/0002/2023 ) funded by the Fundação para a Ciência e a
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at FEUP - FEUP| 1 Bolsa de investigação pós-doutoral |Ciao_2024.16728.PEX Work Location(s) Number of offers available1Company/InstituteFEUPCountryPortugalGeofield Contact City Porto Website https
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announcement also available at FEUP - FEUP| 2 Bolsas de investigação |AWARE_2026 Work Location(s) Number of offers available2Company/InstituteFEUPCountryPortugalGeofield Contact City Porto Website https
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2022.09373.PTDC financed by national funds through FCT/MECI, under the following conditions: Scientific Area: Machine Learning/Recommender Systems Admission requirements: Candidates who cumulatively meet the