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Field
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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machine learning computer models (i.e. algorithms) for medical imaging, bioinformatics (i.e genomics data including single cell and spatial omics) and drug development applications. Performs analysis
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University Assistent position in the research group Bioinformatics and Computational Biology headed by Ivo Hofacker. Our team works on the development of algorithms and methods for problems in Computational
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of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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Responsibilities: Conduct research on differential privacy algorithms with applications in computational processes. Develop innovative ideas to enhance existing algorithms and frameworks. Collaborate on applying
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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to research and teaching in algorithms and computational complexity. While the focus of this appointment is algorithms and complexity, exceptional applicants from all areas of Computer Science will be