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Field
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analysing the outputs of hydrodynamical simulations of clusters of galaxies to trace the build-up of mass through the cosmic network as clusters grow by mergers or smooth accretion of matter along filaments
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? If you’re a HCI researcher, ready and keen to take on these kinds of complex challenges towards real-world impact, we encourage you to apply. If you have any questions, please contact prof m.c. schraefel
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qualifications/experience High level analytical capability Ability to communicate complex information clearly Essential criteria: Demonstrated research experience with publications in top journals (or conferences
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health data. Understanding and/or experience of machine and deep learning (e.g. XGBoost, convolutional neural networks etc.). Flexible, enthusiastic and confident in relating to colleagues of varying
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approaches. - To communicate complex and conceptual ideas to those with limited knowledge and understanding as well as to peers, using high level skills and a range of media. - To build relationships and
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and beyond, and participating in research networks such as the Collections-Connections-Communities initiative. We particularly encourage applicants who will seek to bring new perspectives
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. • Familiarity with BMS development or experience with other complex control systems such as motor drives, power converters, or real-time embedded controllers. • Practical experience in system modelling and
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in using Computational Fluid Dynamics (CFD). Experience simulating complex fluid dynamics processes, preferably multiphase reactive flows, using and especially customising CFD software is an essential
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research associates and PhD students. You will also engage directly with numerous external stakeholders (industry and academia), which will form part of your research network and give you opportunities
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technologies, solve complex problems, and drive meaningful advancements within the Digital Screening and Artificial Intelligence research. The post is offered on a full time (38.5 hours per week), fixed term