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Field
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and the entire Department of Energy (DOE), providing analysis on domestic energy policy. Its work spans technology policy, infrastructure policy, state, local, tribal, and territorial policy, and energy
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accurate and reliable data collection and analysis. -Proficiency in data analysis and report writing. -Excellent oral and written communication skills, with the ability to effectively present scientific data
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interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and
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fairness and robustness for reliable clinical use. 3, Develop AI-assisted robotic guidance tools for precise and automated ultrasound acquisition. Interface AI algorithms with robotic systems to adaptively
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Potsdam-Institut für Klimafolgenforschung e.V. (PIK) | Potsdam, Brandenburg | Germany | about 2 months ago
closely with the principal investigator for PIK’s part of the project, Prof. Dr. Elmar Kriegler. Contribute to the development and analysis of sustainable development pathways and international climate
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operation and maintenance (O&M) protocol for the implemented media filtration system to ensure safe, reliable, and efficient operation. Organize and conduct field missions, carrying out on-site pilot-scale
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of Energy (DOE) experimental facilities. This role involves research and development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high
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Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences (formerly Institute of Genetics and Animal Biotechnology PAS) | Poland | about 1 month ago
English. 6. Proficiency in Microsoft Office and experience with statistical software. 7. Knowledge of bioinformatics tools and functional analysis software will be an additional asset 8. Independence
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using reliable classical reference calculations and extending toward more challenging regimes. As part of our team, you will work closely with ORNL staff and external collaborators in quantum computing
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neural networks, covering representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform