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Field
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. For the working group “Past and Future Earth” (PATH) within the Research Department “Earth System Analysis”, PIK is offering an Early Career Researcher position (PhD or postdoctoral level) (m/f/d) (Position number
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 12 hours ago
field A strong publication record in high-impact venues (NeurIPS, ICML, ICLR, AAAI, ACL, EMNLP, Nature/Science family, JAMA, Lancet Digital Health, or equivalent) Deep expertise in machine learning and/or
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The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep
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monitoring agricultural emissions across Africa using satellite remote sensing, atmospheric modeling, and deep learning. Research Focus Estimate cropland emissions (NH3, N2O, CO2, CH4) using satellite
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learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in collaboration
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modern deep learning frameworks (e.g., PyTorch) and evaluate them with a focus on interpretability, robustness, and real-world applicability in healthcare settings. The role also involves developing
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. Candidates with experience in dimension reduction, deep learning, machine learning, modeling neuroimaging data are especially encouraged to apply. Excellent written and communication skills are required
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of datasets through the JWST Advanced Deep Extragalactic Survey (JADES) collaboration. The postdoctoral researcher will contribute to ongoing JWST programs and collaborative projects, while being
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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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candidate will contribute to projects in one or more of the following areas: influenza transmission and epidemic outbreaks, including developing advanced deep learning models to predict emerging antigenic and