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. Andrea Lecchini-Visintini at the University of Southampton, UK and potentially with other colleagues associated with the project. The post will be full time for 4 months, starting from 1st April 2024
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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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generation precision therapeutics for hard-to-treat cancers. The successful applicant will join a growing interdisciplinary research team working at the interface of supramolecular chemistry and biomedicine
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applications. Combining organic synthesis, photophysical characterisation and advanced biological techniques, this project seeks to deliver next generation precision therapeutics for hard-to-treat cancers
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approaches to understand fundamental biological processes, with the goal of using this information to generate engineered antibodies for use as therapeutics in cancer and autoimmune disease. The appointee is
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. Key responsibilities include: Designing Power Processing and Control Unit, targeting compact and robust power delivery. Developing a PASTA testbed enabling remote control and monitoring. Optimising a
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science to understand how this under-recognised natural resource supports agriculture and rural livelihoods, and how it can be managed sustainably. The role The post is funded by the Leverhulme Trust as
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will lead the natural language processing and language modelling aspects of the project, focusing on how sensor-derived motion data (from radar) can be transformed into linguistically meaningful BSL
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related to staff position within a Research Infrastructure? No Offer Description We are seeking a highly motivated post-doctoral researcher of high calibre to join our research program working in the area
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and rural livelihoods, and how it can be managed sustainably. The role The post is funded by the Leverhulme Trust as part of the project “Quantifying the socio-economic consequences of losing bat guano