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. This scholarship aims to support PhD-level studies on FAE by exploiting a new methodology that combines deep learning technology and knowledge graphs. The goal is to research and develop a new Decision Support
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major research goals are highlighted: (i) the development of deep learning pipelines leveraging longitudinal user health data for knowledge extraction and medical decision support; and (ii
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: Preference will be given to candidates: With a track record of publications related to task planning for robotics. With training and experience in the use of deep learning and large language models
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developing statistical and machine learning approaches for the integration of cancer multi-omics data and the analysis of CRISPR-based screens. Responsibilities include designing bioinformatics workflows
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|2025/795 under the scope of the Project Machine Unlearning in Speech Foundation Models: Learning to Forget (LeaF), Refª 2024.14611.CMU , funded Fundação para a Ciência e a Tecnologia, I.P., is now
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approaches for binarized network models, identifying their strengths, limitations, and applicability within privacy-focused machine learning frameworks. Special attention will be given to evaluating
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systems where the candidate played an active role together with familiarity with deep learning methods. EVALUATION CRITERIA The selection will be based on the following criteria: CV: 50% Experience in