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MRI data from near term pregnancies. As a Senior Research Associate your main contribution will be to develop medical image segmentation and registration algorithms to facilitate the creation
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team. You will lead in the design and implementation of statistical and computational algorithms of different datasets, and implement novel algorithms within the framework of existing code, providing
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, and maintaining software systems to support these research projects. This includes building data pipelines, developing algorithms, and ensuring that data is stored efficiently and is accessible to all
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algorithms. These algorithms act as perfect digital lenses, with no image degradation from aberrations, and provide a fantastically detailed, information-rich view of any sample being imaged. Applications
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machine vision algorithms. The system will be designed with the physical constraints of remote fusion environments in mind, including radiation tolerance, restricted access, and the need for automation and
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procedure. Your key role within the team will be to develop a robotic swabbing system, conduct user studies for efficacy evaluation, and develop automatic swabbing control algorithms. You will have experience
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, drawing insights and ideas for implementation. Having previous publications is a plus. Experience in designing, developing, and implementing computer vision models and algorithms. Proficiency in Python and
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Python programming and computational algorithms is highly desirable. Additionally, you will possess a deep understanding of time-series data processing and analysis, as well as experience in human
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and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected from in-service
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the swabbing procedure. Your key role within the team will be to develop a robotic swabbing system, conduct user studies for efficacy evaluation, and develop automatic swabbing control algorithms. You will have