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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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performing atomistic simulations with Density Functional Theory and Molecular Dynamics. Data analysis and coarse graining in order to provide parametrisations for upper scale models (Kinetic Monte Carlo and
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-0831 Description of Work: At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents
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for reasoning over heterogeneous historical and social data (texts, maps, images, archaeological records), combining causal discovery, multimodal modelling, and agent-based simulation to produce open
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effects of species invasions along environmental gradients and their consequences for community- and ecosystem-level responses, using native and invasive freshwater snails as a model system. The project
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Description We are recruiting a contract researcher to join a project involving the development of predictive models for simulating material forming processes, within the mechanical engineering department
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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) AI, and finally (iii) advanced modelling, simulation and optimisation techniques in a complex uncertain environment for the design of a SAADC. The working approach is based on four successive and
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Fluid Dynamics simulation code developed by our Project Partners at the Barcelona Supercomputing Center. The PDRA will improve and validate an existing model we have developed to simulate analogue dyke
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Network. https://www.eu4greenfielddata.eu/ ***Double Degree PhD Scholarship in Computer Science Opportunity: "Optimization-simulation coupling for the GHG emission estimation based supervision and