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demonstrate proof of concept. You will lead the technical activities related to modelling and experimental testing, including the design of test programmes and interpretation of results. The role will also
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. About the Role: The successful candidate will join a dynamic research team dedicated to designing and developing state-of-the-art microfluidic sensors. These sensors aim to address critical challenges in
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, spectroscopy, and electrical performance measurements. You will work closely with fabrication engineers to translate physical processes into machine learning models, design and train deep learning architectures
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closely with biology and modelling colleagues in a vibrant interdisciplinary team. Key accountabilities / duties You will: Design, set up and deliver robust measurements of plant-generated acoustic
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analyses. Work iteratively with experimental colleagues to guide measurement design, interpret results and perform model validation. Contribute to reproducible modelling workflows (version control
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with acoustics and modelling colleagues. They will have experience with plants, microbiomes, and bees/pollinators. Key accountabilities / duties You will: Design and execute controlled plant growth and
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within the designated area while actively seeking opportunities to apply your findings by engaging with relevant stakeholders. You will be expected to publish your research in reputable academic journals
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vivo imaging platforms. Key responsibilities To work within the Mansour and Roghanian labs, and with collaborators at Southampton and beyond. To design, conduct, and analyse in vitro and in vivo
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Computer Science (ECS) at the University of Southampton. The successful candidate will contribute to an interdisciplinary research programme focused on the design, synthesis, and characterisation of liquid
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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