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and identify green skill gaps within the prison context. Phase 2: Data Modelsling and Structuring: Utilize data analysis techniques (e.g., Python and statistical modelling) to process information
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Research Grant | project Luminous, Ref. 2023.11112.ICDT, from CICECO - Aveiro Institute of Materials
Python, MATLAB or equivalent will also be considered. 5. Eligibility: Applicants are eligible if they comply with paragraph a) of no.1 of article 2, of the Research Fellow Statute as amended by Decree-Law
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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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, Transformers, Python, PyTorch and/or TensorFlow, multimodal fusion); Active and semi-supervised learning; Software engineering for R&D (Git, reproducible environments, large-scale data pipelines). Exclusive
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. For admission and curricular evaluation purposes, proven skills in programming, preferably Python and/or C++; computer vision; computer graphics; real-time 3D rendering; 3D Gaussian Splatting, Mip-Splatting, LOD
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data analysis software (10%), Proven programming skills: Matlab, Unix, Python (30%), Relevant publications in the project area (10%), The correspondence between the candidate's profile expressed in
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skills: Matlab, Unix, or Python (30%), Relevant publications in the project area (10%), The correspondence between the candidate's profile expressed in the letter of motivation and the requirements
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Excel proficiency ii. Dashboard creation and data processing iii. Programming, preferably Python Workplan and objectives to be achieved: Definition of indicators and creation of dashboards for monitoring
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relevant work experience in this area for more than 2 years. Candidates should have experience in written and spoken command of English; good knowledge of Python and Machine Learning; organizational skills
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Reference Number AE2026-0193 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0193.pdf JOB