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Field
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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science, mathematics, physics, or a related field. You have affinity with numerical modelling, preferably atmospheric modelling or climate modelling, and mathematical theory of dynamical systems. You have
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the behaviour of energetic materials both at the microscopic (i.e. crystal deformation and failure) and macroscopic levels. Numerical techniques for the generation of digital twins and modelling
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tools (e.g., drones, 3D mapping) for high-resolution geological mapping and rock mass quality assessment. Develop and calibrate numerical models using field data and case studies to simulate various
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knowledge of energy system modelling or climate modelling Good knowledge of deep learning, PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary
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Numerical simulations of Lattice QCD DoS Dr. Craig McNeile (craig.mcneile@plymouth.ac.uk , tel.: +441752586332) 2nd Supervisor Dr. Vincent Drach ( vincent.drach@plymouth.ac.uk , tel: +441752586335
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that you contribute to the development of the Renovation Digital Twin concept (led by Saxion). Essential activities within your project will be to: · model data standards for design of renovations
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under controlled conditions designed to reveal the underlying mechanisms of biomineralisation in marine calcifying organisms. The task of this PDRA is to assist in the design of a numerical model of
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well as sustainability. Its study model with Leuphana College, the Leuphana Graduate School and the Leuphana Professional School has won numerous awards. For the Institute of Management, Accounting & Finance (IMAF
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to date by validating numerical models against test data, before undertaking parametric studies to investigate the sensitivity of the key variables that affect the flexural performance of composite steel