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focus on agent-based modeling and the quantitative analysis of spatial structures in experimental data. In doing so, you will develop your own research focus, support conceptual work, and contribute
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student to work within the ADaM project (Autonomous workflows for Data-driven first-principles Modelling). The project will leverage Large Language Models (LLMs) as active software agents to help automate
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for the future of mobile and satellite communications. Fields of applications range from 5G/6G telecommunications to satellite-based internet connectivity. For details, you may refer to the following: https
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experimentally verified results is a necessary: Research Topics: Learning-Based Autonomous Systems for Field Robotics Reinforcement learning-based navigation Multi-agent coordination and communication-aware
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to set your own research priorities within the project Desirable skills, but not essential: Initial experience with agent-based modeling, Programming skills Our Offer: We work on highly topical, socially
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in peer-reviewed research articles for publication. Desirable: F1 Experience researching environmental sustainability considerations of business activities. F2 Experience with agent-based modelling
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. Evidence-based Practice Maintains expertise in the ADNP practice model, competency models, and simulation standards of practice. Educates staff on policies and procedures, supporting practice changes based
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. Evidence-based Practice Maintains expertise in the ADNP practice model, competency models, and simulation standards of practice. Educates staff on policies and procedures, supporting practice changes based
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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economic models based on technological building blocks in key economic sectors or on macro-economic data to estimate present and future environmental costs. Economic value of AI and its environmental