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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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This PhD studentship aims to transform how exercise rehabilitation is delivered for working-age adults living with multiple long-term conditions (MLTCs). Partnering with Chiron AI, an NHS-compliant
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About the Project The future power grid will be a highly complex cyber-physical system, integrating multiple distributed energy resources (DERs) such as solar, wind, marine, and bioenergy alongside
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analysis on neuroimaging data\integrate connectome findings across multiple speices work on developing new statistical methods to compare networks across conditions apply bioinformatic tools for integrating
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-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
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environment empowering our people to fulfil their personal and professional ambitions Gender-friendly environment with multiple actions to attract, develop and retain women in science 32 days’ paid annual leave
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in Mathematics, Computer Science, or Statistics Proficiency in one or multiple programming languages (R, Python, Julia, MATLAB) Interest in infectious disease dynamics, public health, global health and
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equivalent in Mathematics, Computer Science, or Statistics Proficiency in one or multiple programming languages (R, Python, Julia, MATLAB) Interest in infectious disease dynamics, public health, global health
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and their cognitive functions and vulnerability to mental conditions. By applying neuroimaging, genetics and network neuroscienceanalyses to MRI data from multiple species, the project aims to study the