42 parallel-computing-numerical-methods-"Multiple" PhD positions at Cranfield University
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BASF, you will gain insight into ecological risk assessment, landscape-scale modelling and regulatory contexts. Cranfield University offers an advanced modelling environment, high-performance computing
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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project will develop novel methods for modelling and controlling large space structures (LSSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. Working with leading
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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validation experiments for modelling • Computational fluid dynamics techniques • Finite element analysis method • Reviewing literature, planning and managing research, writing technical report / paper
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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. These insights will directly inform future nature-positive urban design. If you are passionate about ecological systems, urban sustainability or applying advanced quantitative methods to real-world environmental