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Do you enjoy working collaboratively to understand impact and support continuous improvement? We are looking for a Monitoring, Evaluation and Learning (MEL) Manager to join us on a Fixed Term basis
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This is an exciting time to join the University of Southampton. We have a global reputation for delivering world-class education, research and enterprise that makes a real impact on society’s biggest challenges. The School of Ocean and Earth Science is seeking to recruit a permanent...
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, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques for generating high-resolution climate projections. In addition to developing
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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emerging multi-omic measurements to build and test machine-learning-based multimodal risk prediction tools. A key element of the role will be to explore how different data types and AI-derived features can
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, ensuring a positive first impression. Provide information and signpost enquiries to the right services. Accurately maintain records and use computer systems to support daily tasks. Handle card payments and
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history of innovation in what we teach our students – and what they teach us. We have a strong interdisciplinary tradition, reflected in investments such as UKRI Centres for Doctoral Training innovating
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that intersects with emerging fields such as digital tribology, machine learning for predictive wear modelling, sustainable materials, or tribological challenges in clean energy systems and advanced manufacturing
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calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to Level 4 Spine Point 28 - 30
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in machine learning and prediction/decision modelling, as applied to clinical, cognitive and/or physiological data, as well as with prior experience in participant recruitment and/or experimental