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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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the mentorship of leading experts in one of the following priority research areas: Research area 1: Intelligent Structural Optimization using Physics-Informed Reinforcement Learning Research area 2: AI-Enhanced
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be considered as part of the recruitment process. For further information including key benefits designed to help maintain and support employees' well-being and work-life balance, please see our
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You will join our team at the Optoelectronics Research Centre and work on the Engineering and Physical Sciences Research Council funded project HyMeta: Hyperuniform Disordered Metasurfaces
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that applicants may seek flexible working patterns which will be considered as part of the recruitment process. For further information including key benefits designed to help maintain and support employees' well
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academia or industry, with experience of both is an advantage. The position is funded by the EPSRC (Engineering and Physical Sciences Research Council) project: SUSTAIN - Sustainable heterogenoUs e-textileS
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balance in the workplace. The Faculty recognises that applicants may seek flexible working patterns which will be considered as part of the recruitment process. please see our working with us website page
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methods. It may also include quantitative data analysis. The post-holder will take a role in all stages of this process, from conceptualisation to data collection and analysis, as well as writing up and
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process. For further information including key benefits designed to help maintain and support employees' well-being and work-life balance, please see our working with us website pages.
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) Experience with metabolomics and volatile analyses Experience working with interdisciplinary teams involving engineering/physics measurement or modelling. This post is aiming to start from June 2026 (by