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to estimate their age, but if resorption occurs, it would lead to underestimation and inadequate conservation efforts. Additionally, investigating the role of mononuclear clastic cells in resorption during
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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of generative AI. Essential Skills and Experience A background in a relevant field such as behavioural science, cognitive science, data science, psychology, human-computer interaction, law, or a related
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for estimating sustainable city size by identifying key determinants (e.g., accessibility, agglomeration, emissions, equity), testing spatial boundary sensitivity, and broadening sustainability
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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qualifications in psychology, human factors, artificial intelligence, human computer interaction, or a discipline that could shed light on individual and team dynamics within the context of command and control
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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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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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. This research opportunity will produce policy-relevant, causal estimates of the effects of health preventative interventions on health inequalities. Depending on the student’s interest, potential projects may
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Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering For further information, please follow the link for each Graduate Research Degree ● 3291 - Doctor