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candidates using photometry, spectral energy distributions and, when available, spectroscopic data. Both fellows will produce diagnostic plots and summary tables. Simple statistical or machine-learning methods
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planning and identification of strings and modules in the field. Development of a computer vision and machine learning pipeline for the detection, localisation and classification of defects in photovoltaic
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- One Method Does Not Fit All: Co-design of Context-aware Adaptive Mobile Authentication for Older Adults”, “2024.14974.PEX”, “DOI: https://doi.org/10.54499/2024.14974.PEX ”, funded by the Fundação para a
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programme Reference Number AE2026-0189 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0189
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? Not funded by a EU programme Reference Number AE2026-0205 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt
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Programme under Portugal2030 and the European Union, operation code COMPETE2030-FEDER-02975500 (n.º 24829) taking place at the Department of Informatics of the University of Beira Interior (http
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possible renewals, a cumulative period of four years of research fellowship intended for doctoral students. Preferential factors: Research experience in the areas of Bioinformatics and Machine Learning
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curricular evaluation purposes, proven skills in programming, preferably Python; machine learning and artificial intelligence; language models and retrieval-augmented generation (RAG); ASR/TTS; diarisation
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supporting documentation, proven experience in all of the following areas: natural language processing and machine translation (sequence-to-sequence modelling, NMT, glosses); deep learning, Transformers, and
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. Time-Resolved Spectroscopy will be used to acquire fluorescence decay curves over a range of emission wavelengths to capture the dynamics of fluorescence emission and extract fluorescence lifetimes