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http://www.sussex.ac.uk/epp/ Applications are invited from talented and creative students for a PhD place in Experimental Particle Physics, to join the Sussex group working on the NOvA experiment
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of particle physics (e.g., the existence of dark matter in our universe, or the so-called “g-2” anomaly) will be explored using LHC Run-2 and Run-3 data using the golden “multileptonic signatures”, whereby
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. This project will, for the first time, incorporate nanoscale flow physics within a Brownian simulator of particle motion in channels. In this largely unexplored space we can expect that a complex interplay of
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by chemical and physical interactions at the atom-scale and mesoscale. Modelling of these materials is affected by the choice of filler particles, the particle size distribution, the percentage filler
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of particle physics (e.g., the existence of dark matter in our universe, or the so-called “g-2” anomaly) will be explored using LHC Run-2 and Run-3 data using the golden “multileptonic signatures”, whereby
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single-mode optical fibre. Investigation of machine learning tools for micro-optics design. If you have an interest in photonics, quantum technology, and computer-based modelling, you would be highly
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required to induce unstable growth, the natural frequency and oscillation dynamics under ultrasonic irradiation, and their jetting collapse dynamics. You will learn how to set up, run, and post-process large
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; University of Sussex | The City of Brighton and Hove, England | United Kingdom | about 2 months ago
of particle physics (e.g., the existence of dark matter in our universe, or the so-called “g-2” anomaly) will be explored using LHC Run-2 and Run-3 data using the golden “multileptonic signatures”, whereby
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be using quantum control theory and machine learning methods to improve speed, sensitivity, and resolution of magnetic resonance spectroscopy and imaging. This project will develop skills and expertise
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intelligence (AI) and machine learning (ML) methodologies in order to correlate improved texture with optimized manufacturing and storage processes. The ideal candidate will combine strong experimental and