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Field
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information from high-quality videos that share content with distorted footage as constraints in the learning process of modelling algorithms. This method uses the characteristics and knowledge embedded in high
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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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
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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. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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are working with a PhD student and a research fellow who have collected underwater data and preliminary algorithms. With their guidance and supervision, project aims and objectives are expected to be achieved
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-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org