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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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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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/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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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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Imaging, enabling integrated experimental and single-cell approaches. Human Technopole supports career development through training, mentoring and dedicated learning opportunities. What you'll bring
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. Recent advances in digital pathology and innovative data analytics including machine learning have enhanced our ability to identify clinically relevant spatial characteristics of TMEs [1]. In lung cancer
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correlations between transcript and protein levels. Using machine learning, we will identify conserved expression profiles that predict lifespan outcomes. Guided by these insights, we will use state-of-the-art
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correlations between transcript and protein levels. Using machine learning, we will identify conserved expression profiles that predict lifespan outcomes. Guided by these insights, we will use state-of-the-art
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shaping spatial and temporal trajectories of liver regeneration and cancer. Linking computer simulations with experimental observations will further uncover intrinsic and extrinsic factors shaping clonal