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on the U.S. energy sector. Our research seeks to inform public and private decision-making on issues such as electricity system planning, energy resources and delivery, new large loads, reliability
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“on-the-fly” approaches to efficiently process large volumes of data. The candidate will then perform benchmarking of these techniques to evaluate their performance and relevance for the analysis of airframe
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bioelectrochemistry, a process utilizing electrochemistry to drive redox reactions catalyzed by enzymes. This technology has a large potential ranging from health (biosensors, biofuel cells) to “power-to-X
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field measurements and computationally intensive simulations, limiting their scalability and responsiveness for risk-informed decision-making across large offshore wind farms. This project will develop
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fields such as data science, computer science, and mathematics, that work together to develop innovative methods and tools to analyze large-scale data sets and gain insights into the underlying principles
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-ray scattering, materials science, and/or experimental methods at large-scale research facilities Experience in scientific programming (e.g. Python), data analysis and handling/managing large datasets
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Job description: At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around
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on brain cancer cells. Cancer cell microtubules have large electric dipole moments and are influenced by a process in which an electric field can affect the way in which the dipoles organize themselves in
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representation of streamlines inferred from geomagnetic data, from Finlay et al. Nat. Rev. Earth Environ., 4:377–392, 2023 and numerical simulations by Schaeffer et al. Geophys. J. Int., 211(1):1–29, 2017
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abundant, collectors could build large collections and long time-series of specimens, and correspondingly rich written records. These include notebooks, labels, publications, annotated books, diaries and