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Ultrafast dynamics of Photoactive Metal Complexes for antibacterial applications School of Mathematical and Physical Sciences PhD Research Project Directly Funded UK Students Prof J Weinstein
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on frequencies much higher than conventional magnets and recent advances have demonstrated how they can be efficiently manipulated on these timescales. At faster timescales the interaction of the atomic structure
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harsh environment. This includes constant bombardment by high energy neutrons, which smash into the materials, rearranging the atoms in our carefully engineered metallic alloys. We need to understand how
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New concepts and advanced materials for quantum nanophotonics School of Mathematical and Physical Sciences PhD Research Project Competition Funded Students Worldwide Prof A Tartakovskii Application
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applications. He has particular interests in unconventional machine learning algorithms, computational modelling of physical systems and how paradigms from neuroscience can lead to new ways of computing. His
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speed up the process of masonry bridge construction. The project will also develop advanced digital design tools, targeting digital manufacturing approaches such as CNC carving where complex shapes
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iron pipe retrieved from a case study network to observe changes in corrosion rates, disinfectant residual decay, biofilm growth and detachment rates, and mobilisation of inorganics. Different final
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, such as foundation models, multi-modal learning algorithms, generative models, and large language models [1], have made seen remarkable advancements in the field of healthcare. It can lead to more accurate
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/device development and fabrication, atomic force microscopy and image analysis. The successful candidate will have a 2:1 degree, or above, in either Physics, Chemistry, Materials Science or Electrical
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, computational modelling of physical systems and how paradigms from neuroscience can lead to new ways of computing. His research intersects machine learning and physics, looking to better integrate advances in