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analysis and machine learning methods for optimisation and decision making, to describe the F&V supply chains for various products at regional UK scale and assess their resilience to cascading risks
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engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate future contributions to capacity-building and socio-economic advancement after
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proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris
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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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postdoctoral Research Fellow (RF) position for one year with a possible extension for one more year. The starting date is November or December 2025. This post will advance the application of Machine Learning (ML
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, Recommender Systems, Machine Learning or Artificial Intelligence (applied to text or financial data) A3 A comprehensive and up-to-date knowledge of the wider subject area or subject specialism in Information