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modelling (e.g., LSTMs) and deep generative/unsupervised anomaly detection techniques (e.g., VAEs). *Strong programming proficiency in Python and familiarity with standard data science and machine learning
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methods with the ability to implement and evaluate machine-learning systems at scale. Candidates may come from topological data analysis, geometric deep learning, network science, statistical physics
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