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Organization National Energy Technology Laboratory (NETL) Reference Code NETL-Postdoc-2026-Duan How to Apply A complete application consists of: An application, including academic history, work
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-Projects/index.html ); and (C) the network of SCRIPTS international partner institutions, where the proposed research stay may be hosted (https://www.scripts-berlin.eu/about-us/internationalization
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Business School and the Stockholm School of Economics with a network of collaborating scholars, primarily at European universities. Previous postdocs from the group have gone on to academic positions at well
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. Examples of potential research topics: the democratization of the firm; democratic or economic planning; employee ownership; platform cooperativism or socialism; network states; gov-corps; start-up
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the simulation of turbulent flows using a tensor network representation of the Navier–Stokes equations. Unlike recent approaches based on tensor networks, which simulate fluid flows in physical space using finite
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and stronger professional network, and gain experience in mentorship and academic service. Position Number: RC1460 Anticipated Salary: $63,480 - $90,000 (based on qualifications and experience
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transitions of information flow networks, near critical events. The successful candidate will: Develop and apply Transfer Entropy estimators to high-frequency financial time series. Characterise the temporal
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University of Massachusetts Chan Medical School | Worcester, Massachusetts | United States | 2 months ago
causal networks that govern cellular behavior from large-scale single-cell datasets. Our group has pioneered computational approaches for: • Inferring causal networks from Perturb-seq (interventional
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the collection, coding, management and analysis of qualitative and/or quantitative material. Design and conduct semi-structured elite interviews, including topic guides, participant recruitment, transcription and
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staff position within a Research Infrastructure? No Offer Description Activities: The scholarship recipient will be responsible for implementing and comparing quaternion-valued deep neural networks