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Field
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of students and can include, technique development, microscopy-spectroscopy, analysis/programming (including AI and machine learning) and materials-focused studies. We use innovative high-resolutionidentical
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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, or other related academic discipline. Good programming skills (preferably Python). Background/work experience in Cyber Security, Machine Learning, and Finance would be highly beneficial. How to apply
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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multimodal data, ultimately uniting rigorous machine learning foundations with biological discovery. Project details This PhD project will contribute to the development of generative models for multimodal data
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certification, dramatically accelerating innovation cycles. What you will gain: Expertise in Finite Element Analysis, Scientific Machine Learning, Uncertainty Quantification, and Professional Programming
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using cutting-edge computational techniques, including machine learning algorithms. Work collaboratively with an interdisciplinary and international team to refine and validate regional wave and ocean
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of reinforcement learning or agent-based systems. LanguagesENGLISHLevelExcellent Research FieldComputer science » Computer systemsYears of Research Experience1 - 4 Additional Information Benefits • Full funding
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regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue networks perform well across UK towns and
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: Machine Learning Molecular Dynamics. The project involves the development and application of machine learning methods that enable a major boost of the time and length scales accessible to ab-initio/first