211 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" uni jobs in Portugal
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AçoresCountryPortugalCityPonta DelgadaPostal Code9500-321StreetRua da Mãe de DeusGeofield Contact City Ponta Delgada Website https://fgf.uac.pt/pt-pt Street Rua da Mãe de Deus Postal Code 9500-321 STATUS: EXPIRED X (formerly
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, duly signed and dated, delivered, together with all attachments, through the IPB electronic competition platform (http://concursos.ipb.pt ) and must contain the following elements: a) Full identification
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Reference Number AE2026-0030 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0030.pdf CALL FOR
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and signed application form, available at the following link: https://www.isa.ulisboa.pt/sites/default/files/documents/document/default/form_inv_dl57.docx The application must be addressed
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
reserves the right not to select any candidate if none meet the required criteria. Website for additional job details https://ist-id.pt/ Work Location(s) Number of offers available1Company
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20 Feb 2026 Job Information Organisation/Company Instituto Superior de Engenharia do Porto Department Human Resources Department Research Field Engineering » Computer engineering Engineering
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, of 20 June; b) Be the holder of a doctorate or hold the title of specialist, in the specified area, or in an area linked to the area specified in the competition. Where to apply Website https://ips.pt
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Forjaz de Lacerda, MD PhD, under the research project “Development of CAR T cell therapies against cancer-specific post-translational modifications” funded by La Caixa Foundation, to execute the following
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20 Feb 2026 Job Information Organisation/Company Instituto Superior de Engenharia do Porto Department Human Resources Department Research Field Engineering » Computer engineering Engineering
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physiological signals, with a focus on ECG, and to develop machine learning and deep learning methods for classifying clinical, health, and wellness findings. Supporting project management and research group