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knowledge and proven capacity of data analytics and machine learning. *Excellent programming in Python, R, SQL. Have experience with tools such as Google analytics, AWS, Looker, Tableau, or similar
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integrates spatio-temporal analyses (including synthetic descriptions such as distribution envelopes, size structures, and joint species distribution modeling), trophic modeling, and machine learning
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. Familiarity with frameworks such as TensorFlow and Keras, as well as libraries including Scikit-learn, NumPy, and pandas; - Experience with machine learning models such as Extreme Learning Machine (ELM
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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software for aerospace precision machining — you will develop physics-informed machine learning models that learn how individual machines actually behave, and use those models to drive a genuinely
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on novel applications of machine learning techniques on mobility data towards resilient, safe, inclusive and sustainable urban micro-mobility systems. You will become member of an international, 38-partner
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required. The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, led by Laura Cantini, works at
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mitochondrial quality leads to neurodegenerative diseases and impairs neuronal recovery. To approach these questions we use a combination of genetics, biochemistry, cell biology and imaging in a number of models
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: Alexandre José Malheiro Bernardino (ist13761) Organic Unit: Scientific Area of Systems, Decision and Control Scholarship Theme: Computational Auditory System Simulators and Machine Learning-based Optimisation
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will focus on developing efficient foundation models to medical image analysis. Foundation models offer a scalable and adaptable solution for medical image analysis by learning generalizable