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their quality; vii. Collaborate on projects within the scope of the Communication, Image and Marketing Unit, namely event organisation, merchandising and content production. Contest Procedure Applications must be
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epileptic patients to the analysis of microscope images. This position aims to research and develop biomedical image processing methods for the subsequent application of artificial intelligence methods
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membrane separation processes. Good knowledge of English, and mandatory written and oral proficiency in Portuguese. Selection process Read the job offer at http://www.cebal.pt/images/docs/Posicoes/2026
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) within the scope of the project “HUMYK - Autonomous Community Composter", with operation code CENTRO2030-FEDER-01180100 (Nº 17322), co-financed by Centro 2030 Regional Program, Portugal 2030 and the
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(AutoML) platform to output Machine Learning/Deep Larning models focused on image analysis. In this sense, the focus will be the development of several modules: a module to load, process and store images
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20 Feb 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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attending an academic Bachelor’s degree in the scientific field mentioned above. Knowledge or experience (preferred) on machine learning or computer vision techniques, and interest in developing such skills
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be valued) Proficiency in English and Portuguese; Ability to work with image production software (e.g., Canva), social networks (e.g., LinkedIn and Instagram), and blogging tools (WordPress). 4. Work
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 18 days ago
the nature of the project which is aimed at utilizing cutting-edge technologies, such as Brain imaging, Neurofeedback and Brain-Computer Interfaces (BCI) for neurorehabilitation, the candidate must have broad
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computer vision to analyze photos and thermal images. Objectives include data collection, improving available degradation models, new machine learning-based classification and risk assessment methods, and