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4 Dec 2025 Job Information Organisation/Company University of Beira Interior Department Informatics Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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4 Dec 2025 Job Information Organisation/Company University of Beira Interior Department Informatics Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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visualization (weighting 0.20) - maximum 15 values With knowledge and experience in Python, data analysis, processing, and visualization, time series processing, and machine learning 15 val. With knowledge and
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identification documents)*; Experience in developing Virtual Reality / Game applications; Experience with the UNITY game engine; Knowledge of computer graphics. * mandatory requirement Work plan: The candidate
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requirements: Degree in Computer Engineering, Electrical and Computer Engineering or similar areas; Compliance with the Regulation on Research Grants, in particular with regard to compulsory enrolment in a
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» Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal Application Deadline 18 Nov 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status
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Intelligence Admission requirements: Hold a Master's degree in Artificial Intelligence and Data Science, Computer Engineering, or related fields. Previous participation in research projects in the field
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, for the period from 2021 -2026. Reference: BI/UTAD/116/2025 Scientific area/research field: Engineering Researcher profile: First Stage Researcher (R1) Admission requirements: Degree in Computer Engineering
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of research in the areas of Machine Learning, Models and physiological signal processing; - Criterion 2 – Motivation and interest. VII.III- The evaluation of the criteria and the final classification will be
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Escola Superior de Design, Gestão e Tecnologias da Produção de Aveiro - Norte da Universidade de Aveiro | Portugal | about 1 month ago
Regulations of the University of Aveiro. 5. Work Plan: This project aims to develop solutions based on Artificial Intelligence for optimizing additive manufacturing processes. Machine learning techniques will