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of this fellowship is to contribute to the development of innovative and sustainable models for the promotion of active and healthy ageing in a cross-border context, based on digital solutions and participatory
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). 9.Application process and mandatory documents: Complete applications must be submitted online at https://ccmar.ualg.pt/en/career-opportunities and must include: 1. A motivation letter (in English
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model to be prepared by the fellow is available at the following link: https://ucppt-my.sharepoint.com/:w:/g/personal/ccabral_ucp_pt/ESnbf2LTfxFGj8NsKVEAe3IBi00sddFg238l4P7ziYmXTw?e=olqq3I The report
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
simulations and model review Run medium-scale PIC-QED simulations for selected parameter sets; collect diagnostics (particle growth, spectra, density, absorption). Systematically review and compare existing
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. Admission Requirements: Doctor Degree in Environmental Sciences and Engineering. 4. Other Requirements: Experience in air quality modeling will be valued. 5. Eligibility: Applicants are eligible if they had
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) Research Fellowship for Master degree holder, within the scope of the R&D project “Radio4Breast - Mapping the potential of human breast-on-a-chip models for personalized radiation therapy, reference 16134
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programme Reference Number AE2026-0216 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0216
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requirements: a) Holders of a Master’s degree, with experience in the deposition of thin films or other materials applied to biomedical devices, namely in the acquisition and modeling of biosignals; b
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of stress intensity factor evolution at the crack tip. Concurrently, a numerical model will be developed to complement the experimental results and allow for the calculation of crack propagation rates. Work
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 months ago
of a higher education institution, within the project “Gastric cancer metastasis-on-a-chip (MoC) model as a predictor of metastatic patterns”, ref. - 2023.12556.PEX, financed by national funds through