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position within a Research Infrastructure? No Offer Description Want to explore how citizen collectives can drive societal change? Join us as a PhD in using AI-powered agent-based modeling to design adaptive
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of the following areas: distributed artificial intelligence, coordination and negotiation, game theory and mechanism design, multi-agent learning and reinforcement learning, agent-based modelling and simulation
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spectrometry; radiopharmaceutical dosimetry with novel agents and/or software techniques; alpha particle RPT radiation biology modeling and analysis of clinical trial data. For additional information on a subset
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behaviours of multi-agent systems in response to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be
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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
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at obtaining further academic qualification (usually PhD). Research area: Systems of interacting particles are ubiquitous in natural and social sciences. Typically, they comprise many agents that, through intra
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Your Job: In the CrowdING project, you will develop agent-based movement models that realistically simulate different behaviors such as lining up, overtaking, or pushing. Based on this, you will
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to evolve advanced, human-centered AI technology to empower human learning, including designing, developing and evaluating systems and models to enhance learning through AI technology. The PhD fellow will
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into different types of neurons. In this PhD project we will work to further develop these human stem cell-based models as a platform for robust and reliable identification of neurotoxic agents. To achieve
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We are seeking a motivated and creative PhD student to explore safe and trustworthy planning under uncertainty in multi-agent systems. They will collaborate on interdisciplinary research which draws