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degree, in the scientific area of Biomedical Sciences, Biology, Biochemistry, Psychology, Biomedical Engineering, Computer Engineering, Physical Engineering, Electrical Engineering; Clinical Neurosciences
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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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of Biomedical Sciences, Biology, Biochemistry, Psychology, Biomedical Engineering, Computer Engineering, Physical Engineering, Electrical Engineering; Clinical Neurosciences, Neuroengineering enrolled
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machine-learning methods for sample segmentation and classification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will join the INESC TEC team within the LIBScan project, carrying
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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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, Economics, Management, or related fields. [1] ; Be a student enrolled in a doctoral program in Computer Engineering or Computer Science - a requirement to be duly proven at the time of hiring. 2; 3. Preferred
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: Research experience, with an emphasis on socio-territorial studies and the use of quantitative and qualitative methods, as well as the use of computer applications for qualitative processing and analysis
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Programa Financiador: PITD Scientific Area: Electronics Engineering Recipient category: Masters in Industrial Electronics and Computer Engineering, or related areas Type(s) of scholarship to be awarded
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that do not confer an academic degree, in the area or area related to that requested in the tender. Preferential factors: Have demonstrable experience in the use of machine learning algorithms applied
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(current or prospective) Master's students who have achieved excellent results in their Bachelor's studies, and who pursue Master's level studies in Artificial Intelligence, broadly conceived. Academic