454 algorithm-development-"Helmholtz-Zentrum-Geesthacht" PhD positions in United Kingdom
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- VIN UNIVERSITY
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to cancer biology, as well as a strong commitment of developing and using new tools to address cutting-edge questions in these fields. This studentship is embedded within the piRNA team, consisting of both
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projects. The role will also provide the opportunity to learn and develop medicinal chemistry skills as applied to drug design. The role is ideal for someone who has, or is about to be awarded, a PhD in
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the MRC Centre for Neurodevelopmental Disorders. At the Centre for Developmental Neurobiology (CDN), we investigate the mechanisms governing the formation of the brain during embryonic development and in
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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mechanical fatigue—individually and sequentially, followed by electrical breakdown testing to assess their impact on the dielectric performance of the material subsystems. The target is to develop a
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, introduces human error, and creates line-of-sight occlusions, disrupting surgical workflow. This interdisciplinary project aims to overcome these challenges by developing a vision-based marker-less navigation
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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, curious individual to join an exciting PhD. This opportunity is generously funded by John Crane Ltd, a world-renowned engineering technology leader. Why This PhD? Impact Clean Energy's Future: Develop next
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? Mechanical seals are critical components in high-pressure storage solutions for hydrogen and carbon capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational
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railway earthworks. Additionally, the project will integrate environmental data through data fusion and develop automated machine learning tools for anomaly detection and risk assessment. The effectiveness