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The Role Applications are invited for a Postdoctoral Research Associate in Computer Science with a particular emphasis on structural and algorithmic graph theory. The purpose of the role is to
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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the Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences (NMES). The department is internationally recognised for its contributions to robotics, AI, and human-centred
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the Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences (NMES). The department is internationally recognised for its contributions to robotics, AI, and human-centred
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Application Deadline 16 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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qualified in relevant subject area (or nearing completion) Good knowledge of computer vision algorithms for image and video processing Strong experience in machine learning or deep learning for medical image
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse
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. You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. An excellent scientific track record proven