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for this PhD project consist of combining empirical studies in healthcare environments, such as observations and interviews, with prototype design and development. The project will develop new knowledge on how
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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, you will develop and deliver an independent research project exploring ethical issues at the intersection of global health and infectious disease. The role-holder will contribute to collaborative
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Sciences Institute (PSI), part of the Nuffield Department of Medicine. Reporting to Dr Tess Johnson and working closely with the Ethics, Policy and Context Theme, you will develop and deliver an independent
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challenges, such as technological development requiring rare minerals, and mitigation and adaptation to climate change. Knowledge is needed of these processes of landscape change, their driving forces and
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detection and automation. The UMLFF project aims to develop next-generation MLFFs with built-in uncertainty predictions to enable safe, automated active learning and create broad, reliable MLFFs. You will
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. This PhD project aims to develop efficient, reasoning-enhanced Vision–Language Models tailored to multimodal medical data. The main aim is to investigate how explicit clinical reasoning can be embedded
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Turbulence detection in blood flow using 4D MRI Flow disturbances in blood flow are vital sign of cardiovascular diseases, suggesting a development of turbulent flow due to abnormal heart movement
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 11 days ago
: Large-Space Gaze Analysis via Multi-camera System for Social Interactions” to develop datasets and algorithms to capture and analyze eye gaze. About the project We are supporting the development of highly
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at the intersection of theory, computation, and high‑fidelity simulation, the successful candidate will contribute to the development of a novel ensemble-based framework for analysing driven perturbations in wall