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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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river system Develop, test and apply algorithms for the processing and analysis of satellite data drawing on the latest physics-based and/or data-driven techniques Contribute to work on the automation and
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for a 3-year fixed period, ideally starting in November 2025 or as soon as possible thereafter. Informal enquires should be directed to Prof. Anna Peacock (acp@orc.soton.ac.uk). Applications
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signal processing Extensive research experience and scholarship on radar systems and signal processing, ideally for distributed radar sensors, and general knowledge of the effects of oscillator
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the Neurogenesis and Brain Cancer group led by Prof. Simona Parrinello. The team uses a variety of state-of-the-art technologies, including advanced imaging, single cell and spatial ‘omics’, barcoding, mass
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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analytical techniques, with a focus on quantifying energy output and sensitivity to initiation by external stimuli. The project will be jointly supervised by Prof. Colin Pulham in the School of Chemistry at
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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here, https://www.gov.uk/guidance/academic-technology-approval-scheme . The appointment is for 36 months, starting as soon as possible. Informal enquiries are welcomed and should be directed to Prof