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Field
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life cycle analysis methodologies. Proficiency with modelling and simulation software relevant to TEA and LCA. High analytical ability to analyse and illuminate data, interpret reports, and bring new
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, simulation, prototyping, and pre-clinical validation of a novel temperature-insensitive, 6-degree-of-freedom force sensor for use in minimally invasive cardiac surgical instruments. This patented technology
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development of next-generation computational tools for simulating particle-laden two-phase flows by integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics
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individual to work on an exciting modelling and simulation project, involving extensively applied work at the intersection of software engineering research and modelling and simulation, with real-world testing
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learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial analysis Strong publication record Experience in women and children’s
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and healthcare system simulation modelling will be useful for evaluating these options. To that end, this team will develop a novel analytical simulation framework and use it to address these pressing
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or use existing simulation platforms to validate the developed algorithms and models. Analyse simulation data, and create visualizations to support research findings. Design and build prototypes
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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research to generate research outputs of high standard Development, fitting, simulation and parameter recovery of computational models Communicate research findings through scientific publication in peer
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and wellbeing programme and an evaluation of the feasibility and acceptability of a novel remote monitoring model in rheumatoid arthritis outpatient services across south-east London. The post-holder