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requirements: Candidates must hold, at the time of application, a Bachelor’s degree in Informatics Engineering or related fields. Candidates must also have knowledge in: i. Deep Learning and LLMs: practical
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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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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://www.di.ubi.pt ), under the following conditions: Research Field: Machine Learning/Pattern Recognition Objectives: Unsupervised Incremental Representation Learning for Ground-Based Drones in Dynamic Industrial
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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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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and Machine Learning/Deep Learning Applications for Low Amplitude Transient Signal extraction: this project explores the use of AI, ML/DL techniques to explores several sources of signals with