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to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About
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science and translational research models SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and experimental models that bridge laboratory discoveries to clinical
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energy data lifecycle spans pre-construction (e.g., meteorological mast data, LiDAR data, wind climate and energy yield modelling, environmental impact assessment data), operational phases (e.g., SCADA
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or compromised IoT devices by analysing encrypted traffic patterns, focusing on metadata, flow characteristics, and timing rather than decrypting payloads. The core challenge is creating features and models
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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undertake comprehensive literature and market surveys, develop advanced simulation models, investigate integration into HVDC transmission systems, and design/test scaled-down hardware models at the ‘Wolfson
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used to measure motion and deformation. It provides comprehensive full-field deformation data, essential for analysing complex materials, structures and model validation. The DIC community has developed
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noise models, leading to metrics devoid of assumptions about noise impacts (e.g., cross-talk or non-Markovian noise in gate fidelities). As shown by the supervisory team, non-Markovian noise can be a
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background in physics, biophysics, biological physics, or bioengineering. This PhD project will primarily focus on experimental research, which will include data analysis and there is scope for modelling
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to explore these projects and the results coming from them, the latter involving the modelling and follow-up of any high probability events. The student will also explore the most promising methods