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Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on
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links) and Space Domain Awareness (tracking satellites, debris, and near-Earth objects). Expanding AO to these domains introduces challenges: extreme performance for faint or high-contrast targets
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. The appointed candidate will join an MRC-SA/MRC-UK funded project whose objective is to address and understand the role that the water, wastewater, animal waste systems and food, plays in the transmission
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research. The postdoc will lead one or more discrete projects with a clear set of research objectives that will result in first-authored publications. In addition, we expect the postdoc to develop additional
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Ability to acquire new skills beyond current expertise to achieve project objectives. In-depth theoretical and practical knowledge in engineering or cell biology. Ability to work independently and
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the project lead peer reviewed outputs relevant to acoustic tracking and project modelling objectives, and other objectives as appropriate. About you The University values courage and creativity; openness and
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) or other expertise relevant to the project objectives (see above) Early career track record including publications or other outputs in the related field In case your background is in psychology or medicine
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settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on obtaining external funding and project
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(e.g. Python, R) Experience in the use of neuroimaging analysis (fMRI, MRI) to study mechanisms of brain function Previous experience of using Bayesian methods in both model development and fitting
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of using Bayesian methods in both model development and fitting. Previous experience and knowledge of research methods and study design in clinical trials. Knowledge of Good Clinical Practice (GCP) in