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charlesliye新蟲 (小有名氣)
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英國南安普頓大學(xué)博士全獎(jiǎng) - 混凝土材料+AI - 力學(xué)/土木
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AI-Driven Durability Design of Sustainable Concrete for Marine Infrastructure 申請鏈接：https://www.findaphd.com/phds/pr ... astructure/?p188612 This project develops AI-assisted models to predict the durability of sustainable, low-carbon concrete in marine environments. Combining advanced characterisation of alternative cementitious systems and carbonated concretes with interpretable machine learning, it enables faster, more reliable design of long-lasting marine structures, advancing the transition to Net Zero and circular construction. The ultimate goal is to create a transparent, data-driven durability design tool that links mix design, microstructure, and exposure conditions to long-term performance. The outcomes will accelerate the development and adoption of circular, low-carbon concretes for marine infrastructure, directly supporting Net Zero and sustainable construction objectives. What's in it for you? - join a world-leading research group at the University of Southampton focused on marine and sustainable infrastructure - gain expertise in durability testing, microstructural analysis, and AI/ML modelling for materials prediction - address real-world challenges in marine sustainability, offshore engineering, and Net Zero construction - build a strong foundation for a career in academia, materials R&D, or data-driven infrastructure design. You will receive training in cement chemistry, marine durability testing, microstructural characterisation, and machine learning for materials design and prediction. Through the Doctoral College, you will also develop transferable skills in scientific writing, communication, and research management, with opportunities for teaching, collaboration, and international research exchange in sustainable construction. Required qualifications - 1st or 2:1 honours degree (or international equivalent) in civil engineering, material engineering, mechanics, computer science or a related field. - high motivation, self-direction, and a proactive approach to research. - excellent communication and teamwork skills for effective collaboration. - IELTS 6.5 (or equivalent) for non-native English speakers. Preferred qualifications - experience in cementitious materials, micromechanics, machine learning, or characterization. - proficiency in coding and computational tools (e.g., MATLAB, Python, FEA, CAD). - strong academic writing skills for producing high-quality research papers. - prior involvement in research projects. |
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