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for data augmentation, small language models, anomaly detection using learning methods, and explainability techniques for decision-making. The research will involve designing and developing prototypes
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or equivalent Skills/Qualifications Valued/Preferred qualifications: Experience in software solution development Experience with machine learning models Experience in R&D&I projects (Research, Development and
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structural bioinformatics, machine learning, and high-performance computing, we will build the first Human Proteome-Wide Frustration Atlas — a resource to better classify genetic Single Nucleotide Variants
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on the application of machine learning in satellite communications (20 points). Participation in European Space Agency projects (20 points). Other skills that are valuable, but not mandatory are: Knowledge of over
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the development of components using agent-based modeling techniques, reinforcement learning, and other explainable artificial intelligence modules for decision-making, situation assessment, and operational support
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activity, oxygen storage capacity), in collaboration with machine learning experts to build predictive models. Producing well-characterized nanoparticle batches for external testing and catalytic
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of this annex, as well as to: Programming in Python and R. Statistical classification and machine learning methods: SVM, neural networks and logistic regression. 3.2. Qualification: Official Master’s degree in