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such as Education and Technology (EdTech), Human-Computer Interaction (HCI), Natural Language Processing (NLP), or Applied Artificial Intelligence. Demonstrable projects (e.g. GitHub repositories
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Explore machine learning approaches for discovering interpretable and clinically relevant visual representations.; • Validate the proposed methodologies
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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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the field of architecture or related fields; Proficiency in computer-aided design, graphics and video software, as well as data processing and word processing software, amongst others; Advanced knowledge