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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 opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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covers fees and stipend for a home (UK) student with funding provided by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme. Options exist for PhD and Master + PhD routes
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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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. 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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This fully-funded PhD research opportunity, supported by EPRSC Doctoral Landscape Awards (DLA) and Cranfield offers a competitive bursary of £22,000 per annum, covering full tuition fees. This PhD
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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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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves