Sort by
Refine Your Search
-
. This project aims to develop machine learning models to predict a particle shape and size for a given chemical formulae and crystallisation method. Extractive Language learning models developed will be able
-
, investment casting processing, computational modelling of casting processes at a macro-scale / component level and at a dendritic growth level, and machine learning methods for process optimisation. The ARCANE
-
interdisciplinary researchers to grow ideas from concept through to manufacture, instrumentation, and testing, alongside advanced computational mechanics, machine learning, and data analytics workflows. For more
-
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
-
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
-
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
-
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
-
computational mechanics, machine learning, and data analytics workflows. For more information on the facilities, a virtual tour is available. The dynamic group (>20 PGR students and Research Staff) leverages