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and machine learning concepts, such as data preprocessing, model evaluation, embeddings, classification, regression, or clustering. Ability to learn new tools, frameworks, and technologies quickly
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machine learning (ML), artificial intelligence (AI), operations research, data science, and industrial engineering, with applications to aviation, healthcare, sustainability, supply chains and
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; agent learning and adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer
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; agent learning and adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer
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support; agent learning and adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer
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, alongside machine‑learning and deep‑learning frameworks for pathogen detection, drug‑target identification, antimicrobial discovery and protein‑protein interaction characterisation. Working
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) Associate / Full Professor in Applied Mathematics / Statistics Ningbo, China Professorship (W2) in Statistical & Machine Learning in Life Sciences + Research Group Lead Munich, Bavaria, Germany
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mathematics, biostatistics, advanced statistical techniques in clinical research, database management, and machine learning/artificial intelligence (AI) would be an advantage. The appointee will work with the
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award winners are preferred Research experience and practical background in Machine Learning or AI4SCI. Candidates with experience in cutting-edge deep learning research (e.g., GNNs, Transformer-based
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transportation systems, transportation data analytics, AI/machine learning, Web-based transportation systems, or database development; Strong programming skills in Python, C++, MATLAB, Java