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Field
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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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will play a leading role in the analysis of large and complex genetic and electronic health records datasets with a range of Statistical and Machine Learning approaches, whilst leading a broad range of
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PhD Project: 3D-printing next-generation electro-actuators for soft robots and devices Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive
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embedded AI systems. They will demonstrate a strong track record of high-quality research in machine learning/AI and/or embedded systems, evidenced by publications in leading conferences and journals
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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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real-world deployment scenarios and collaborate with global organizations to ensure practical implementation and scalability. Key Research Areas: Software engineering, AI/machine learning, IoT
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, from Undergraduate Degree level to PhD, and much more in between. We are currently recruiting for an inspirational Lecturer in Special Educational Needs, Disability and Inclusion. We are seeking
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postgraduate-level research in Computer Science, Cybersecurity, Information Security, Information Technology, Artificial Intelligence, Machine Learning, or a related field, have experience with securing AI
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instance, Machine Learning and AI, Big Data Analytics, Statistical Modeling, Data Visualization, Data Security, Cloud Computing, Applied Data Science in Healthcare and Environment, Data Engineering