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Field
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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project called Policy Modelling for Health. This fully funded PhD place provides an exciting opportunity to pursue postgraduate research in population health modelling, estimating health outcomes and health
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to/ lead the development and implementation of quantitative analysis and statistical modelling to support the project’s aims of assessing the contribution of An. stephensi to malaria transmission relative
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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, gather relevant data for modelling, and ensure accurate data collection. Conduct comprehensive bioinformatic analysis utilising established methodologies and tools (e.g. R, Python, MATLAB and other
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class is a collection of models that includes the random growth of a surface over time or the behaviour of a large number of particles that move around in space and interact with each other according
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this fundamental challenge, the PhD candidate will be part of a wider team to establish methodological framework, combing utilisation of controlled tree growth test, thermodynamic modelling and advanced optical
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. For example, anaerobic bacteria culture and human cell co-culture infection models; cell viability assays and cancer invasion and migration assays; ELISA, quantitative PCR, DNA damage assays