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coordination (e.g., disasters), remote and distributed workplaces (e.g., virtual organisations), and management of civil infrastructure and services (e.g., aviation). In C2 settings, teams of heterogeneously
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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uptake and adherence, and the modelling of future health inequalities by building tools for distributional cost effectiveness analysis. Integrated PhD Program As a candidate in the Centre for Health
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will design quantum-safe threshold encryption and/or authentication algorithms. The expected outcome is the design of methods, techniques and their software prototype to implement quantum-safe threshold
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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
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, programming, algorithms, and data analysis skills Outstanding research skills Applicants with Master degrees by research with technical publications and research experiences in structural dynamics and
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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determined by combining the observed space density of galaxies, the measured spatial distribution of galaxies and simulations of the dark matter distribution. Example themes for student projects follow and
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres