20 machine-learning-"https:"-"https:"-"https:"-"https:" positions at The University of Southampton
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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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, 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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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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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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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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candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use this experience in collaboration with
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testing) Design mechanical parts (using SolidWorks or similar), produce via 3D printing or machining Build calibration rigs and other supporting lab setups as needed Test the devices in the lab. Deploy
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cell mechanisms, oversee preclinical validation, and advance CAR-iNKT platforms optimised for AML immunotherapy. The role bridges basic and translational research and suits a creative scientist with
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An exciting opportunity is available for a talented researcher to join a successful team in Primary Care Research Centre/Clinical Experimental Sciences to develop an e-learning tool for clinicians