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As Computational Senior Research Fellow, you will: · Develop cutting-edge methods to predict which somatic mutations drive clonal expansion · Integrate large-scale multimodal omic datasets from healthy
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and validate a prototype microscope with enhanced sensitivity and contrast, evaluate label‑free and fluorescence imaging modes, and develop robust hardware/software workflows for low‑light measurements
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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the development of excellent doctoral and postdoctoral training programmes and collaborative research projects worldwide. By doing so, they achieve a structuring impact on higher education institutions, research
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the UK) and work within the Department of Cancer and Genomic Sciences. Their main role will be to apply and develop new methods for precise genome manipulation to create transgenic reporter models
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Propose and develop state-of-the-art methods to overcome existing problems. Train and evaluate the models and systemically compare them with recent models. Prepare papers and reports. Develop systems based
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, including deep neural networks and physics-informed neural networks, to analyse large datasets from gyrokinetic and fluid simulations of plasma turbulence Develop and train reduced-order models that capture
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enable real world application. Fellows will gain hands-on exposure to translational science, drug discovery, and technology development, with opportunities to contribute to intellectual property
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plus standard bank holidays and five university closure days including closure between Christmas and New Year. · We are committed to staff development through the provision of training, continued support
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of human embryonic development, especially regarding the emergence of the body plan. Research in the Developmental Models laboratory aims to uncover the principles of human development using cutting-edge in