791 phd-in-architecture-interior-design-built-environment PhD positions in United-States
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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to increase each year. Tuition fees will also be paid. Home students are eligible. A funded PhD studentship is available in the field of computational inorganic chemistry. The project will involve prediction
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techniques will be needed to design architectures the next generation of resilient systems under this increased complexity and growing risks from cyber-attacks. The focus of the PhD project is to identify
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transportation. An important aspect of this is the interior environment of the vehicle, particularly the ways in which vehicle occupants experience tranquillity. Many factors influence this, including multi
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passengers luxurious transportation. An important aspect of this is the interior environment of the vehicle, particularly the ways in which vehicle occupants experience tranquillity, serenity and calm. Many
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global change, damaging critical infrastructure resilience. This project is part of the prestigious Loughborough University Vice Chancellor’s PhD Cluster – RAINDROP (Resilient eArthwork INfrastructure
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Award Summary 100% of home tuition fees paid and an annual stipend (living expenses) at the UKRI rate (£20,780 for 2025/26). This funding is designed to support Home students only. Overview
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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into the co-design of ultra-low-power AI hardware architectures tailored for edge computing applications. The research aims to develop neuromorphic processors, FPGA/ASIC-based AI accelerators, and intelligent