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. At a glance Application deadline01 Apr 2026 Award type(s)PhD Start date01 Jun 2026 Duration of award3 years EligibilityUK, EU, Rest of world Reference numberCRAN-0039 Entry requirements Applicants
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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. At a glance Application deadline01 Apr 2026 Award type(s)PhD Start date01 Jun 2026 EligibilityUK, EU, Rest of world Reference numberSATM606 Entry requirements Applicants should have an equivalent
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
We are pleased to announce a self-funded PhD opportunity for Quantitative assessment of damage in composite materials due to high velocity impacts using AI techniques. Composite materials, such as
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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value. Yet these trade-offs remain poorly quantified in complex urban landscapes. This PhD will investigate how urban blue networks can be optimised for both ecological resilience and community wellbeing
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This PhD offers an exciting opportunity to tackle one of Europe’s most urgent biodiversity challenges – amphibian declines driven by interacting pressures from agriculture, climate change and
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applications for a PhD studentship focused on developing and validating innovative origami-paper eDNA sensors with community scientists for the rapid detection of chemical and microbial contaminants in rivers
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems