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researcher for a two-year position within the ADaM project (Autonomous workflows for Data-driven first-principles Modelling). By leveraging agentic Large Language Models (LLMs), the project will develop
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/she will also take part to beam test campaigns (CERN, DESY, Mainz, FermiLab or BNL) and will be involved in simulation work (GEANT4) of exclusive processes, such as Deeply Virtual Compton Scattering
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems for viral agents. Emphasis is placed on determining
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AI agents (cloud-based and edge AI) and related tools for cold supply chains. Participate in and/or lead stakeholder engagement efforts. Supervise and collaborate with graduate students in laboratory
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projects that will provide ground-breaking technological advances based on ultrasound transducer arrays. At the Imaging Physics Department, Faculty of Applied Sciences, we develop innovative measurement
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. • Familiarity with MODFLOW, MATPOWER, OpenDSS, Machine Learning based emulators, or agent-based modeling. • Knowledge of scenario development, resilience frameworks, and socio-environmental-technological systems
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economic structures. Quantitative and Computational Skills: Proficiency in computational tools and data analysis (e.g., Python, R, agent-based modeling) for developing economic simulations and analyzing