113 web-developer-"https:" "https:" "https:" "Newcastle University" PhD positions in Portugal
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for the Treatment of Patients in Transition from Acute to Chronic Kidney Disease”, Projeto n.º 15554 (COMPETE2030-FEDER-00660600) co-financed by the European Regional Development Fund (ERDF), through the Innovation
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Framework Programme? Not funded by a EU programme Reference Number AE2025-0551 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https
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15617 (COMPETE2030-FEDER-00669100) co-financed by the European Regional Development Fund (ERDF), through the Innovation and Digital Transition Thematic Programme (COMPETE 2030), under Portugal 2030, with
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- Application Instruction The application must be completed by filling in the respective application form, which is available at https://www.fct.unl.pt/en/faculdade/concursos/investigadores . The application
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FieldEnvironmental scienceEducation LevelBachelor Degree or equivalent Research FieldEnvironmental scienceEducation LevelMaster Degree or equivalent Additional Information Website for additional job details https
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form, which is available at https://www.fct.unl.pt/en/faculdade/concursos/investigadores . The application process must be instructed with the documentation in Portuguese or English. The application
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(Index 33) specialized in integrated wildlife monitoring, to develop an R&D agenda in the area of wild-game resources, with fieldwork experience and integration in research teams in Ecology and Health
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of fund-raising activities and resource mobilization from public, private, and philanthropic entities; 5. Support for the development of strategic partnerships with academic institutions, companies, and
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be available. 11. Application deadline and form of presentation of applications: The competition is open from 02/03/2026 to 13/03/2026. Applications must be submitted electronically at: https
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, with a view to developing and carrying out the above-mentioned project and related scientific activities, with a particular focus on the development of analytical models (data science – machine learning