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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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of nanofabricated sample supports and tracking algorithms for 5D electron diffraction (5DED). EMAT is one of the leading electron microscopy centers in the world and has a vast expertise in both fundamental and
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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will develop autonomous on-board guidance algorithms for space missions using open-source numerical solvers for convex optimisation developed at the University of Oxford. The focus will be on designing
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic