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://scholar.harvard.edu/laibson/home https://faculty.som.yale.edu/jameschoi/ http://www.hbs.edu/jbeshears Principal Duties and Responsibilities: Performing statistical analyses on large databases Designing and running
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hydrogen storage, downstream processes, and energy demand, to enable more efficient, flexible, and economically viable Power-to-X operation. This position is expected to start from 1st of November 2026 or as
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electrode and electrolyte materials, characterize them, evaluate and improve them with respect to battery performance, and study fundamental chemical processes and properties using both experimental and
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to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain. Smart and Sustainable Resilient Performance-based Cementitious Composites for Adaptive Strengthening and
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interaction, and to determine the extent to which this synchrony is associated with the quality of the social bond between partners. To address these questions, we will study young and older adults performing
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interact with other participants in the project. • Responsabilities • Perform research on Platynereis and Ascidian larvae to investigate pressure sensory systems using neurobiology and genetics approaches
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measurement approaches, establish experimental test arrangements, characterise fabricated devices and analyse their performance. The work will involve hands-on laboratory characterisation using high-frequency
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the activities associated with the PhD project to be defined in consultation with the PhD supervisors. Participate actively in the activities performed by the research group (group meetings, seminars,..) Provide
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activation, reliability, robustness and the fact that they are maintenance-free. Despite these many advantages, the exact mechanisms that control performance in industrially utilised thermal batteries has
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 18 hours ago
for: Analysis of phenotypic, microscopic, PET/MRI, MALDI-MSI, and LC-MS/MS data Development of AI-based models for personalized risk assessment Validation and application of model performance using established