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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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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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on lth.se. https://www.lth.se/english/study-at-lth/phd-studies/ Subject and project description We are recruiting 1-4 students for the following two projects: Dual Control at Scale: Learning-based control
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thinking, agent-based modeling, and system dynamics, thereby linking advanced AI with methods for analyzing, simulating, and designing complex socio-technical systems. You will design and investigate methods
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to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be employed to achieve an appropriate trade-off
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-quality educational programs in Computing Science, we are now seeking a PhD student with a focus on agent-based modelling. The Department of Computing Science has been growing rapidly in recent years, with
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research (85%) and education/training (15%). The research component will focus on the development and validation of CAR T cell–based therapies designed to eradicate minimal residual disease and treatment
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data analysis and grant preparation • Experience with agent-based models, statistical methods, artificial intelligence, process modeling, and data visualization • Experience working in teams with people
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integrate the use of Large Language Models (LLMs), LLM agent, Agentic AI models and automated reasoning approaches for the interpretation of complex data, the analysis of experimental protocols, and the
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four (4) years of post-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with