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) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed
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–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
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EPSRC ReNU+ CDT PhD Studentship: Physics-informed machine learning for deep geothermal systems under uncertainty. Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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Andres Floto and his group members. Key responsibilities include working on deep learning, deep generative modelling, and molecular design. Additional responsibilities include developing research
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respectively, we seek highly motivated candidates to develop innovative methodologies for radar sounder data processing, with a strong emphasis on artificial intelligence and deep learning. The research activity
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tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
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tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
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software. Familiarity with deep learning platforms (e.g. TensorFlow, PyTorch). Funding and eligibility The project is fully funded by DSTL, due to funding requirement this studentship is only available
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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segmentation, target detection and change detection along and across multiannual series of data. Methodologies like foundational models, machine learning, deep learning, multitask learning, enforcement learning