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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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design. One of our group's goals is to create efficient surrogate models that reduce the computational cost of MD simulations by several orders of magnitude. Notable examples of our work in this area
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to methods and principles aimed at understanding and modelling the mechanics of deformable bodies. Solid mechanics is a core discipline in mechanical engineering and is of fundamental importance to many other
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computational simulation techniques are used. The research is applied to understand orthopaedic problems and to develop better methods to improve tissues regeneration. The group encompasses about 15 scientists
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postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological capabilities, with a profound potential impact for Europe’s next generation of research and
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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We are seeking a highly motivated and skilled Postdoctoral researcher with interdisciplinary expertise to develop risk assessment and mitigation models using Large Language Models (LLMs
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research, addressing the big data and artificial intelligence challenges of our industry partners. Field of subject for the position: Computer Science Placement: Department of Computer Science and Media
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. Demonstrated skills in Python programming, or other computer programming. Strong interest in data science, such as data collection and curation, modelling. Excellent written and oral English communication skills
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The Camunas-Soler lab is opening scholarships for two Postdoctoral Research Fellows to join our interdisciplinary research team (www.camunaslab.org ). These positions are part of a broader program