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Field
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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and PhD students on computational mathematics and AI methodologies. Job Requirements: A PhD degree in Applied Mathematics, Computer Science, Engineering, or a related quantitative field. Deep expertise
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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Engineering in the 2025 QS World University Rankings by Subjects. The EEE Rapid-Rich Object SEarch (ROSE) Lab focuses on research in: (i) visual search & retrieval, (ii) video analytics & deep learning, and
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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. • Contribute to interdisciplinary research projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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duties incidental to the work described herein. Job Requirements PhD in a related scientific area (e.g., AI, Deep Learning, Machine Learning, Statistics, Database, Bioinformatics, Computational Biology
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability