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Field
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. The research undertaken includes the interpretation of collider data and theory support for LHC phenomenology and future colliders. The Research Associate will be working on beyond the Standard Model
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combines simple, predictive mathematical and biophysical modelling with long-lasting experimental collaborations to dissect biological mechanisms too complex to unravel by experiments alone. In many cases we
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capabilities o Demonstrated experience with machine learning and/or statistical modeling o Expertise in handling large-scale, complex datasets with strong data wrangling skills o Strong publication record
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) computational and AI-guided modelling. Our international collaborative network provides unique opportunities for cross-disciplinary training in innovative methodologies at the interface of neuroscience and
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articles Co-developing new models and methods in the form of education and health toolkits Coordinating impact related activities with stakeholders Collecting impact evidence Social media and publicity
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+ signalling). The project will dissect and characterise intercellular communication pathways to build a model of how megakaryocytes and platelets interact. The experimental design will increase the complexity
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experience of the implementation and critical assessment of idealised and/or complex atmospheric numerical models good communication skills and the disposition to collaborate effectively with both internal and
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to enable robust robot autonomy in complex, real-world environments. The post sits within our EPSRC Programme Grant in Embodied Intelligence and will advance the state of the art in localisation and scene
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modelling applied to biology. About you The successful applicant will be able to present information on research progress and outcomes, communicate complex information, orally, in writing and electronically
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develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung infection. As part of this work, the postholder will