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PhD: Systematic Exploration of Robot Behaviours for Manufacturing Tasks to Automatically Discover Failure Scenarios EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering
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Would you like to work at the intersection of transportation, robotics and machine learning to design mixed fixed-flexible transport networks? Job description The increase of public transport usage
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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of metabolic network modelling linked to epigenetics Carry out machine learning, and integrative analysis of large epigenome datasets Communicate research results in international conferences and journals Work
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parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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student will become part of a team at DTU with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs