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. ISO 13485, ISO 14971, IEC 60601, UK MDR) is desirable, as well as experience of applying signal processing or machine learning methods to physiological or sensor data. Application details: Applications
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and evaluation of the developed methods using relevant imaging datasets and downstream computer vision tasks. This appointment is subject to UCL Terms and Conditions of Service for Research and
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/2026 Priority Review Date (Note - Posting may close at any time) Job Summary University Connected Learning (UCL) is seeking a Computer Technician to configure, deploy, and maintain computers, AV, and
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matching, optimal transport or cell-cycle modelling. Key Responsibilities These include but are not limited to: Leading an independent research project in scientific machine learning and mechanistic
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to: Develop AI and machine learning workflows to analyse microscopy and high-content imaging data from advanced in vitro models. Build computer vision pipelines for image segmentation, tracking, phenotypic
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hours in the space allocated to the group in London (fully remote work is not possible). The postholder can expect: Provision of a quiet work space, a computer, access to high-performance computing, a lab
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combining high-plex imaging, spatial data analysis, and machine learning. One arm of the project will seek to engineer diverse quantitative features (e.g., adapting concepts and metrics from network science
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protein expression across tissues and developmental stages, quantifying correlations between transcript and protein levels. Using machine learning, we will identify conserved expression profiles
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and cellular mechanisms shaping spatial and temporal trajectories of liver regeneration and cancer. Linking computer simulations with experimental observations will further uncover intrinsic and