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particle formation for atmospherically relevant molecules. ORCTOOL (Organic Cluster Tools) aims to create a toolbox for understanding and cost-effectively predicting the rate of massively multicomponent
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be monitored with an ensemble of 1D pressure sensors and event cameras in a Particle Image Velocimetry (PIV) setting, to record the changes of large-scale velocity flow field. Event-based vision is
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fundamental research in particle physics, astrophysics, geophysics and accelerator physics. It is part of the Physical Sciences Division (PSD). The EFI is also involved in training the next generation of
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-Energy Theory at Harvard University Applicants are invited for research positions in high-energy theory (including but not restricted to particle physics, particle astrophysics, quantum gravity, quantum
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at the nano- and larger scales, with applications in particle therapy, radiotherapy, and radioprotection. These include the formation of DNA strand breaks by ionising radiation, DNA repair, radiosensitisation
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optimisation algorithms for quantum routing using genetic algorithms (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO), optimising cost functions subject to entanglement fidelity
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Modeling, Analysis & Prediction of Particle-laden Real-Gas Supersonic Turbulence. (Ref. 10267290001)
. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-research-s… Requirements Research FieldEngineering » Mechanical engineeringEducation LevelMaster Degree
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the European Research Council (ERC-CoG2025). Main tasks: This project aims to develop smart imaging agents based on single particle tracers to image alterations of the blood flow dynamics in cancer by positron
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of SOA particle deposition and fluxes onto forest vegetation. As a Doctoral Researcher (PhD Student), you will focus on: identifying new stress-induced volatile organic compounds (VOC) precursors from
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, enabling clear observation of precursor activity prior to failure. High-resolution optical imaging will be used for detecting particle motions throughout the loading process using particle tracking and