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academic research in machine learning and computer vision with direct industrial application. You'll be tackling the real-world problem of data scarcity by developing novel methods using synthetic data
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research experience to include: Experience developing novel deep learning methodologies (e.g. transformer models, Convolutional Neural Networks, Auto-encoder models, or LSTM networks). Demonstrable ability
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, Pathology or in the final stages of PhD submission Knowledge and experience in R and Python computer coding Knowledge in tissue histology Expertise in immunostaining and tissue imaging Track record of writing
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of subsurface processes. You will be responsible for leading the development of the approach, which could include transferring learning from other geographic regions and data types, machine learning methods
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? This PhD project offers a unique opportunity to apply machine learning to solve a critical engineering challenge within the railway industry. The Challenge: Rail grinding is a crucial maintenance activity
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, artificial intelligence, or a related discipline. Expertise in statistical modelling and/or machine learning, with experience applying advanced methods to complex, large-scale health or administrative datasets
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measurement; Measurement of related tracers (e.g., Radon); Programming (e.g., R, Python) for advanced atmospheric time-series analyses, including machine learning; Skills for presenting research at scientific
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Butts’machine learning sub-group. Supporting the development of grant funding applications around machine learning for structure elucidation. You hold a PhD (or are in final stages of preparing to submit for a
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opportunity to design and implement novel digital technologies in collaboration with a wide range of academic collaborators. You will be part of a larger team of Research Associates, PhD students, and a
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machine learning pipeline to derive governing equations and boundary conditions for macroscopic crowd models from synthetic and real-world data. Close collaboration with a dedicated PhD student, who is