12 parallel-programming "Intelligent Systems Group" Fellowship positions at CRANFIELD UNIVERSITY
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conceptual advances in aeronautics, propulsion & power, cyber-physical systems and intelligent automation. Through the strong links with industry built over the past 75 years, we focus on defining and
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enthusiastic researcher to develop advanced modelling and optimisation methods to support the transition towards lower-carbon, more efficient and resilient transport systems and AI enabled circular
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change will exacerbate these problems as low soil moisture reduces plant-availability of P. In natural systems, most plants rely on root symbioses with mutualistic mycorrhizal fungi for efficient P
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change will exacerbate these problems as low soil moisture reduces plant-availability of P. In natural systems, most plants rely on root symbioses with mutualistic mycorrhizal fungi for efficient P
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experience developing deep learning models using frameworks using PyTorch and possess strong Python programming skills. Experience working with Remote Sensing datasets and geospatial technologies such as
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twins, such as sensing, data handling, physics and AI modelling, software development, as well as experiments at the Cranfield Ocean Systems Laboratory. You will also be involved in assessing the
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critical challenge in the UK’s Connected and Automated Mobility (CAM) sector: delivering robust, cost-effective perception systems capable of safe operation in complex, real-world environments. To achieve
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innovative treatment options for low energy ozonation and advanced oxidation systems in drinking water. This research will look at low energy systems such as light-emitting diodes (LEDs), microbubbles for
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systems or electrodialysis. The ideal candidate will have expertise in: Experimental research related to water treatment processes, ideally in the field of coagulant recovery, membrane processes or
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research in automated vehicle modelling and control systems. As a key aspect of this role, they will have the unique opportunity to gain hands-on experience in developing and testing automated