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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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). 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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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 24 hours ago
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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verbal. Preferred Qualifications: Experience combining large clinical and research data sets. Interested and comfortable working with pediatric patients with special needs. A track record of publications
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to self-organize into complex structures. Our approach is to develop sophisticated mathematical models – informed by state-of-the-art biological knowledge and experimental data – to understand
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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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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