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. Experience with AI/ML algorithms and prediction model development. Familiarity with data structures, algorithms, software engineering best practices, and computational efficiency is highly desirable
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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contributions in one or more of the following key areas: computational modeling of chemical systems, AI-driven materials discovery/design, robotics for chemical synthesis, machine learning applications in
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Systems and Control division focusing on data-driven control methodologies. About the research project Model-based control is arguably the prime framework to perform certifiably-safe regulation of dynamical
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for Technology DevelopmentCountryPolandCityWrocławPostal Code54-066StreetStabłowicka 147Geofield Contact State/Province Lower Silesian City Wrocław Website https://port.lukasiewicz.gov.pl/ Street Stabłowicka 147
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-driven cost analysis that informs early project definition, scope development, and delivery method decisions across the capital portfolio. This role ensures that project budgets are credible, comparable
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Environment Water Research Centre (EEWRC) The Climate and Atmosphere Research Centre (CARE-C) The Science and Technology Driven Policy and Innovation Research Centre (STeDI-RC) Considerable cross-centre
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of internationally visible, foundational research in AI-driven semantic structure extraction, automated reasoning-flow modeling, and adaptive content generation. The research focuses on methods for analyzing and
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software development. E3 Experience in training deep learning models relevant in research projects at scale. E4 Experience of applying good software engineering practices including but not limited
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colonize distant tissues using mouse models, in close collaboration with the Bentires Lab at the University of Basel. This project is fundamentally driven by hands-on experimental in vivo mouse work