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Field
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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required Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow) Experience with unstructured
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schools, IMD bridges cutting-edge research with real-world application to help leaders solve problems, scale solutions, and drive impact. Real Learning for Real Impact. To reinforce our team in Singapore
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research, formulate hypotheses, and design effective experimental plans. Strong programming skills with deep learning frameworks (e.g., PyTorch). We regret that only shortlisted candidates will be notified
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models • Strong experience in spatio-temporal deep learning and ensemble techniques • Proven ability to publish research in international peer-reviewed journals • Experience with interdisciplinary
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. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning architectures (CNNs, RNNs). Experience with explainable AI (e.g., SHAP, LIME) is preferred
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deep learning (segmentation and foundation-model architectures) Demonstrated ability to design and execute technical projects Scientific independence with clear interest in biological mechanisms and
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You hold a PhD in Computer Science, Artificial Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep
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the research activities entrusted to the officer take place: This ANR project lies at the interface between statistical learning (mainly deep learning) and combinatorial optimization (mainly stochastic and
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Mathematics, or a related field A strong background in image/signal processing, particularly in computer vision. Strong programming skills and experience with at least one deep learning framework e.g