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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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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
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may also explore embedding these new computational methods into optimisation and machine learning contexts. The new computational techniques developed will be geared towards the following key
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the Centre’s datasets and using data analytics and machine learning, this Centre strand will build a blended data resource that can help to gauge the prevalence, forms, and distribution of slavery in wars
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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cutting-edge machine learning methods for spatial omics and for multi-modal data integration. The post-holder will also collaborate on the development of new computational methods to support the CoRE’s
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an expert in the use of advanced statistical inference and machine learning methods for the analysis of omics datasets. You will work with a team of data scientists in Manchester and Oxford to create tissue
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. The Manipulation and Touch Lab investigates manipulation in humans and robots, haptic sensing, haptic interfaces and machine learning. More information may be found at: https://www.imperial.ac.uk
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the centre. Successful applicants will have (or be about to obtain) a PhD in computational biology or computer science, with knowledge of multimodal spatial omics data integration and machine learning
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental