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, Korea, The Republic of [map ] Subject Area: Physics / Particle Appl Deadline: 2025/08/06 11:59PM (posted 2025/07/07, updated 2025/07/06) Position Description: Apply Position Description Korea Institute
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following areas would be ideal candidates: (1) Quantum matter (2) Particle & Nuclear Physics and Cosmology (3) Soft Matter, Chemical & Biological Systems (4) Pure & Applied Math & Theoretical Science
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, United States of America [map ] Subject Areas: Cosmology/Particle Astrophysics Astrophysics / Astrophysics , Astrophysics and Gravitational Physics , Black holes , Computational Astrophysics , Cosmology , Dark Matter
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: Position Type: Postdoctoral Position Location: Kingston, Ontario K7P, Canada Subject Areas: High Energy Astrophysics experimental particle physics or experimental astrophysics Appl Deadline: 2025/09/30 11
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, United States of America [map ] Subject Areas: Cosmology/Particle Astrophysics Astrophysics / Astrophysics and Gravitational Physics , Black holes , Computational Astrophysics , Cosmology , Dark Matter Appl Deadline: 2025
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bosons, and searches for new physics beyond the Standard Model. The group has a long-standing history of contributions to the development and calibration of b-tagging for long-lived particles, large-R jet
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which will quantify and develop a mechanistic understanding of how environmental controls drive fine sediment impacts for freshwater biota. Fine sediment (typically defined as particles <2mm) deposition
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and mean flow simultaneously. The question of investigation is how floating microplastic particles are transported into the atmosphere via droplets produced by wave breaking, and will involve a
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of field studies and cultivation and growth of plants/ fruits, and filter construction and maintenance as related to the research project. Participant will learn about scientific and laboratory setup
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 1 day ago
, with application to biomedical flows (e.g. microcirculation) it is now intended to develop an improved algorithm for advanced particle tracking using machine learning. The algorithm should be tested in