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: https://www.microman4health.eu/ ). (Data-Centric MicroManufacturing Platform for Added Value in Health Sector). MicroMan4Health pioneers a data-centric micromanufacturing framework for added value in
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engineering stimulated by recent developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with
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development, electronics and the development of data analysis pipelines incorporating machine learning. In collaboration with biological partner groups, the developed system will be benchmarked and applied
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machine-verifiable proof (or certificate) of correctness. However, a major limitation of current techniques is that correctness is not proven relative to the human-understandable specification
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. To achieve this ambitious objective, we will build on recent breakthroughs in proof logging, where solvers do not just output an answer, but also a machine-verifiable proof (or certificate) of correctness
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developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with the running infrastructures. Using
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funded, international doctoral position within the Marie Sklodowska-Curie Doctoral Networks (MSCA-DN) project MicroMan4Health (Website: https://www.microman4health.eu/ ). (Data-Centric MicroManufacturing
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-order modelling, surrogate models, and machine-learning methods such as neural networks. Control design for flexible reactor operation. Develop advanced control strategies that enable safe and efficient
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apply advanced signal data analysis approaches, including machine learning and AI-based modelling Quantify early brain maturation markers and relate them to visuomotor developmental outcomes Work closely
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. Three connected threads make up the research: Discovery: what patterns hide across the facets? - Using unsupervised machine learning (clustering, dimensionality reduction), topological data analysis and