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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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Applications are invited for a fully funded fixed-term position at the Research Associate (PostDoc) level in de-risking cirrus modification. Cirrus cloud modification (CCM) could in-theory mitigate
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Partnership at the University of Cambridge. This programme is a collaboration between industry and academia, now in the final 24 months of a 60-month effort. The programme integrates research and innovation
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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is a willingness to work collaboratively with the wider team. If you like the idea of working as part of an interdisciplinary team that is helping bring cloud computing to the world of genetics-based
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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(NOₓ), and contrail-induced cirrus cloud formation. Aviation currently accounts for approximately 3.5% of total anthropogenic radiative forcing, with non-CO2 effects responsible for around two-thirds
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significantly reduce the amount of vibration data to be stored on edge devices or sent to the clouds. Hence, this project's results will have a high impact on reducing the hardware installation and operation