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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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), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas, SHAP, TensorFlow, etc.) y específicas de análisis de imágenes, estadística, simulación, entornos cloud (tipo Kubernetes
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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
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and