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that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer
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-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration applications
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internationally recognised for its research in craniofacial biomechanics. Located in UCL Mechanical Engineering and supported by state-of-the-art imaging and material characterisation facilities, the lab focuses
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under real-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration
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inversion of gravity gradient data, contribute to the development of data interfaces for multi-modal sensor integration, and perform advanced data processing and inference to support subsurface imaging and
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translation of innovative miniature, hair-thin imaging devices we have previously developed (doi.org/10.1117/1.JBO.29.2.026002 ). These devices are designed to enable early and accurate detection of cancerous
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We are seeking an ambitious and highly motivated postdoctoral researcher to help develop the next generation of fibre-based optical imaging and spectroscopy tools. This EPSRC-funded role is central
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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scientific boundaries and overcome hurdles. They will have experience in stem cell culture, imaging, molecular biology, genetic engineering and/or bioinformatics analysis. This will enable new approaches
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translation of innovative miniature, hair-thin imaging devices we have previously developed [https://doi.org/10.1117/1.JBO.29.2.026002]. These devices are designed to enable early and accurate detection