14 algorithm-development Fellowship positions at CRANFIELD UNIVERSITY in Ireland-University-Ranking-2024
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algorithms for automated driving. You could also develop your own research portfolio by supervising MSc individual research projects aligned with the Centre’s research themes. You will be expected
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-world environments. To achieve this, we will integrate multiple radar units into autonomous vehicle platforms and evaluate perception algorithms in diverse scenarios. The successful candidate will work
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Apply by: 12/10/2026 Role Description About the Role We are looking for an enthusiastic researcher to develop advanced modelling and optimisation methods to support the transition towards lower-carbon
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to help develop the next generation of AI-powered remote sensing technologies for monitoring landscape change and environmental sustainability at scale. About the Role We are seeking an ambitious
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-on experience in developing and testing automated driving functions for our existing automated driving platform, CONRRAD , developed as part of the previous UKRI project Driven by Sound . You will be responsible
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into many novel aspects of developing offshore digital twins, such as sensing, data handling, physics and AI modelling, software development, as well as experiments at the Cranfield Ocean Systems
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of mycorrhizal fungi with plant P and water status, the development of the root system and the broader community of soil microbes. With partners at Cambridge University and in Germany and the US, we will work from
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using techniques such as X-ray micro-computed tomography and X-ray Absorption Near Edge Structure (XANES). You will also undertake laboratory-based imaging and develop analytical workflows to process and
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(XANES). You will also undertake laboratory-based imaging and develop analytical workflows to process and interpret complex 2D and 3D datasets. Working closely with the research lead and an
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responsibility is to conduct cutting-edge research on a new class of biochemical sensor development for wastewater, especially on the single-cell and single molecule detection, utilising state-of-the-art