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of [map ] Subject Area: Condensed Matter Physics / Condensed Matter Physics, Electronic Structure, Strongly Correlated Materials Appl Deadline: none (posted 2025/02/17) Position Description: Position
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the study of the structural performance of buildings. Internal Application form(s) needed Offre d'emploi_POST DOCT 2025_ISTERRE_SHINE TATOO_VF.pdf English (968.69 KB - PDF) Download Additional Information
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
process modeling) and laboratory wave tank experiments to explore turbulent seawater dynamics adjacent to ice. Opportunities may also exist to participate in planned field campaigns in Greenland
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research on AI-driven form finding of structural surfaces under extreme loading. The research will be conducted under the direction of Professor Sigrid Adriaenssens in a team. Candidates with a strong
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molecular dynamics, enhanced sampling, and kinetic modeling—the team investigates how neurotransmitters like norepinephrine and hormones such as estrogen interact with β-adrenergic and estrogen-related GPCRs
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. The positions will push forward the emerging field of Geophotonics — a novel paradigm that explores the interaction of light with natural crystalline materials to decode the dynamics of Earth's surface
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We are seeking a Postdoctoral Research Associate to support our projects to understand membrane evolution. The aim of this project is to use molecular dynamic simulations to understand membrane
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. The ability to work critically with archaeological and ancient historical sources. A methodological and structured approach to work. Good organisation skills and excellent attention to detail. Flexibility and
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and structures that leave many people and places out of the Low Carbon Living agenda. The Centre is accelerating research-informed action that engages, enables and empowers marginalised people
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a