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integrating statistical-mechanical theory, quantitative modeling, and experimental single-molecule methods. We aim to develop mechanistic models of receptor activation that combine physical theory with data
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department, with active theoretical and experimental research in condensed matter and AMO physics, as well as correlated condensed matter, quantum materials, driven/dissipative systems, and quantum information
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applicants for a two-year postdoctoral fellowship in history of medicine and medical humanities. The fellow will have teaching and administrative responsibilities in the department's online program in
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wording. https://diariodarepublica.pt/dr/legislacao-consolidada/lei/2004-58216179 Regulations for Research Grants of the Foundation for Science and Technology in force https://diariodarepublica.pt/dr
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for medical physics residency training and become a clinical medical physicist or faculty afterward. More information about a clinical medical physics career can be found on the following website: https://w3
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Immersive Networking Lab (SINLAB), a multidisciplinary team working on systems that enable users to act in remote physical spaces and experience the effects of their actions through multimodal feedback (audio
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[map ] Subject Areas: Atomic Molecular and Optical Physics Physics / Atomic Molecular and Optical Physics , Condensed Matter Physics , Quantum Information Science , Quantum Optics , Quantum Science
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Hong Kong University of Science and Technology, Physics Position ID: HKUST-Physics-POSTDOC_WATANABE [#31526] Position Title: Position Type: Postdoctoral Position Location: Hong Kong, Hong Kong [map
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/ Machine Learning High Energy Physics Electrical Engineering Nuclear Physics Particle Physics (more...) Cosmology/Particle Astrophysics Appl Deadline: 2026/03/11 03:59 AM UnitedKingdomTime (posted 2026/02
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 15 hours ago
conditions: Scientific area: Bachelor’s Degree in Systems Engineering. Work plan: Model-based digital twins supported by physics-informed machine learning for multiphysics modeling. 1. Grant duration and