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within the Centre for Digital Innovations in Health & Social Care, you will join an active research centre and will be collaborating with researchers as part of a programme of research concerned with
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. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development
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, regulators, and firms to develop sensible policies and innovative well-being initiatives — which will close significant gaps in industry practices and help to create a more resilient workforce. Applicants
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and brain tissue mechanics to improve stroke treatment. Stroke is a leading cause of death and disability worldwide, making advancements in its diagnosis and treatment highly relevant. Computational
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computational mechanics or multiphysics modeling, with particular interest in fracture mechanics and chemo-mechanical degradation. Knowledge of solid-state defect chemistry (advantageous). You will join a dynamic
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the drivetrain. Alternative machine topologies such as axial flux, transverse flux, and homopolar designs offer unique advantages by enabling 3D flux paths, novel cooling strategies, and increased architectural
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timely opportunity to rethink the role of the electric motor within the drivetrain. Alternative machine topologies such as axial flux, transverse flux, and homopolar designs offer unique advantages by
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in a more accurate analysis of optimizing the service performance. Computer vision approaches such as ones for object identification and action recognition can help to automatically identify deviations
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complimentary computational studies to predict the intake aerodynamic characteristics and aid in the experiment design. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based
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important questions such as: Are the patterns that drive AF stable or do they change over time? How do the heart’s layers interact during AF? Can stimulating the heart during normal rhythm help predict