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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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Project Description: This EPSRC-funded PhD project will investigate how next-generation electric and autonomous vehicles can operate as symbiotic agents within the urban ecosystem—intelligently
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control strategies integrating fuel, engine, electric machine, and energy recovery systems for improved overall efficiency. Validate the developed methods through experimental and simulation studies
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avenues by enabling chronic, gut-based monitoring of neuroendocrine activity for applications such as closed loop therapeutics. The proposed PhD project sits at the interface of biomedical engineering
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There is widespread concern about the negative impacts of plastic and other anthropogenic solid waste (hereafter referred to as ‘plastics’) on global biodiversity (Law, 2017; Lau et al., 2020). Such materials are extremely slow to break down, which has resulted in discarded micro- and...
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Northwest Eurasia owes its anomalously temperate climate to the oceanic circulation cell known as the Atlantic Meridional Overturning Circulation (AMOC). Regional warmth is maintained by northward-flowing Atlantic surface currents – including the Gulf Stream – that lose their heat...
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A competition-funded PhD studentship is available in the School of Chemistry at the University of Birmingham to develop and apply nuclear magnetic resonance spectroscopy and imaging to advance
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between these molecules to engineer new quantum states. However, so far it is not well known how to achieve entanglement with molecules with such plasmonic systems. This PhD project will focus on developing
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Join the University of Birmingham for groundbreaking PhD research to make 6G possible! Future radio communication systems (6G and beyond) will use frequencies above 100 GHz to achieve bit rates
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of Sentinel-2 fluvial scenes’. Earth Surf. Process. Landforms, 45, 3120–3140. Carbonneau et al 2020) ‘Adopting deep learning methods for airborne RGB fluvial scene classification’. Remote Sensing of Environment