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potential uses for Machine Learning. Multiscale modelling is important: phase transitions can often be found in the particle models and studied via bifurcation analysis at the continuum level. These
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. Department of Energy and Process Engineering We conduct research and teaching covering the entire energy chain, from resources to the end-user. We look at how energy is produced and used by humans and machines
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24th April 2024 Languages English English English The Department of Energy and Process Engineering has a vacancy for a PhD candidate in airflow distribution, heat/mass transfer and ventilation in
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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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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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: The main task will be related to the analysis of the new Belle II data with focus on rare decays of B-meson and CP-violation, using modern machine-learning techniques to maximise the analysis reach
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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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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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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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complete educational program for PhD students; Multiple courses on topics such as leadership for academic staff; Multiple courses on topics such as time management, handling stress and an online learning