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Kogias as part of his ERC Starting project titled CloudNG (https://cordis.europa.eu/project/id/101220079 ). The post will be based in the Department of Computing at Imperial College London at the South
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quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
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monitoring. • Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions. • Analyze and optimize structural performance and predictive
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Modelling (WCPM) . Find out more about the research group at https://koczorbenda.wordpress.com/ Requirements and eligibility: Applicants must have, or be predicted to obtain, a good degree (2.1 or 1st class
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the specific characteristics of viscoelastic fluid models, which will provide a dataset for training the tensor-based neural network (TBNN). Subsequently, the TBNN model will be tested on deformation protocols
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neuroimaging data constrained by patient's structural connectivity and tractography • Using the results of the TVB model fits to stratify patients and predict disease progression • Organizing and unifying
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to combine high-throughput metabolomics with 3D cell culture models Perform large chemical and genetic studies in cancer cell lines derived spheroids Develop predictive model of drug response by comparing 2D
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that enhance the development and evaluation of advanced analytical models using health data. This includes methods for prediction, explainability, prediction under intervention, algorithmic fairness, transparent
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, Griffith J et al A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure. JAMA. 2011;305(15):1553-1559. Runx1 and Heart Failure Supervisors: Dr C Loughrey , Dr S Nicklin , Ewan Cameron
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and graduate levels (minimum grade of 16 out of 20). Good oral and written English communication skills are required. Experience in computational modeling (DFT and ab initio) with benchmarking