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the mechanical behavior of these materials at the nanoscale. Subsequently, a molecular dynamics model will be developed to simulate the matrix–nanotube interaction, analyzing the effects of adhesion, orientation
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: Develop data-driven numerical models (opinion models, norm dynamics, multi-agent systems). Network Science: Study social and temporal interaction networks using network physics tools. Simulation: Conduct
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equations (SDEs) are widely used to model time-evolving phenomena in finance, biology, and social dynamics, the underlying data is often highly sensitive. This project tackles the intersection of complex
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, focusing on AI- based quantitative imaging of human hemodynamics, as well as neural network models of nonlinear ultrasound for imaging and quantitative tissue property estimation. The outcome of
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, focusing on AI- based quantitative imaging of human hemodynamics, as well as neural network models of nonlinear ultrasound for imaging and quantitative tissue property estimation. The outcome of
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: Set up a high-fidelity end-to-end simulator for the Drag-Free Attitude and Orbit Control System. Set up a linear modelling framework for frequency domain design and verification using linear fractional
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, simulation or systems modelling, data science on health or healthcare, broader economics etc.. Essential Application & Interview Experience in use of data & evidence to populate parameterise a model e.g. by
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nonlinear, ultrafast, and integrated photonics. Develop predictive theoretical and computational models for optical materials and photonic devices. Perform numerical modelling and simulation of optical
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programs emphasize technical expertise and the interdisciplinary applications of computation, modeling & simulation, and data-driven discovery. Complementing its educational mission, CDS faculty develop
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services