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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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mouse handling. Application Materials Cover Letter, CV and references Application Deadline This position will be open until filled Community Information Columbia offers small-town friendliness with big
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interdisciplinary applied research projects. From technological innovation to the transfer of research to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information
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). This consortium pulls together expertise from all over the University, including in diagnostics, data science, drug and vaccine design, preclinical testing and clinical testing and brings it to bear on tuberculosis
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Wide Data-Driven Circular Economy of Industrial Robots”. The candidates are expected to have experience with robotics, artificial intelligence, and digital twins. We are looking for candidates who can
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural
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RibFrac, the RSNA pulmonary embolus CT dataset, or the RSNA abdominal trauma CT dataset, or are otherwise technically proficient with imbalanced cross-sectional imaging data are especially well-suited
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(AIMBE) in 2024, and as a Fellow of the American Association for Dental, Oral, and Craniofacial Research (AADOCR) in 2025 Community Information Columbia offers small-town friendliness with big city
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real