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, control, and interaction for real-world robotic systems Deep learning, multimodal learning, or large-scale AI systems Demonstrated experience in robot deployment, experimentation, and applied AI development
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on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools
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Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Skills/Qualifications Knowledge • Solid understanding of machine learning, deep learning, and modern AI techniques
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. The BlueMat project ?Multiscale Operando Super-Resolution Imaging of Water Imbibition in Hierarchically Porous Materials? aims to establish methods for super-resolution imaging using deep learning. You will
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to Dr Duo Chan. About You Given the interdisciplinary nature of the post, we welcome applications from candidates with a PhD (or equivalent) in Artificial Intelligence/Machine Learning, or climate science
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development. Research objectives This project proposes developing an integrated digital twin platform that bridges experimental characterisation, multi-physics modelling, and deep learning to enable predictive
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(or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply
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. Stefanos Zafeiriou can be found at https://wp.doc.ic.ac.uk/szafeiri/ . Research Associate: A PhD (or be close to completion) in an area pertinent to the subject area, i.e. computer vision, machine learning
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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no
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related to staff position within a Research Infrastructure? No Offer Description Salary package: Level A Step 6 (PhD Awarded Rate) $109,272 p.a., plus 17% employer's superannuation and annual leave loading