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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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networks, with a focus on carbon emissions reduction and network telemetry. You will contribute to the development of a framework that reduces the carbon emissions of networks through the use of carbon-aware
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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in a manner that supports a research-led and scholarly approach to student learning and assessment in the discipline and/or profession. 3. Participate fully in examination and other assessment
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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet
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climate scientists and artificial intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine
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observation-based climate datasets. In addition, we will also use innovative machine learning tools to evaluate the relationship between a set of hypothesised climatic precursor conditions, called (potential
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based