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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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The application for PhD admission will only be assessed where the applicant is successful in being awarded the scholarship The applications for HDR admission and the scholarship are separate processes; applications
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will help increase the material recovery rate in the LIB recycling process and reduce waste and carbon footprint in the battery value chain. By returning waste to battery manufacturing, the project will
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PhD Scholarship in Integrated Photonics for Telecommunication, Biosensing and Precision Measurements
will be trained is some of these different skills: Micro/nanofabrication Simulation/design of optical components Integrated photonic circuits Programming skills in Python, C/C++ Theory of electromagnetic
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other national, international longitudinal studies, and administrative data sets, to examine the mechanisms and processes of key social and emotional core competencies that can be cultivated in schools
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. Degree and/or knowledge of core chemical engineering disciplines such as reaction engineering, kinetic and process simulation. Excellent written and verbal communication skills. Problem-solving experience
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processes; applications for admission to candidature are submitted electronically (link below). Prior to submitting applications, prospective applicants are advised to contact the Project lead, Professor Lily
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for this scholarship and project) a copy of electronic transcripts a CV that includes any publications/awards, experience relevant to the project and the contact details for 2 referees Potential candidates should
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learning in simulated and indoor/outdoor environment. Reasonable results can be achieved in high signal-to-noise ratio environments; further research is required to improve deep learning in fast variation