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analysis, code testing, and system robustness testing. Opportunities include industrial engagement, international collaboration, and exposure to regulatory challenges, providing a strong foundation for
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(Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI workloads demand high performance processing, large scale data handling, and specialized hardware accelerators
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· leave the ‘Research Area’ field blank · select ‘PhD Energy Materials' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: · a
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computer simulations by developing fundamentally innovative and advanced protection strategies. To enhance the reliability and safety of low-voltage networks with a high penetration of power-electronic
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field of multiphase flow modelling. Contact Dr Nadimi (sadegh.nadimi-shahraki@ncl.ac.uk) for more information. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4 Years Application Closing
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behaviour and system efficiency. Uncertainty is inherent in the design of subsurface energy technologies, particularly during early-stage development when data may be sparse, incomplete, or inaccessible
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the programme of study You will then need to provide the following information in the ‘Further Details’ section: · A ‘Personal Statement’ (this is a mandatory field) - upload a document or
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-balancing under stress) and Autonomous Transportation (modeling traffic systems during cyberattacks). This includes creating an Adversarial Scenario Library to curate edge cases like data poisoning and
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Electronic Engineering (Bio-electronics) (full time)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: a ‘Personal Statement’ (this is a
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) and Edge Computing are undergoing a major transformation. Systems that once relied heavily on cloud-based processing and passive data collection are evolving into distributed networks of intelligent