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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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, Mathematics, Computer Science, or a related quantitative field Have strong modelling, computational, and code development skills Have experience with network science, multi-agent systems, statistical mechanics
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of genetic loci and chromosomal rearrangements. • Develop and analyze individual-based (agent-based) models programmed in SLiM or C++ to test the robustness of analytical results (e.g., accounting for genetic
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fragmentation. This project seeks to overcome these barriers by integrating BIM-based energy modeling, semantic data models (Ontologies), and Large Language Models (LLM) into the control workflow. The candidate
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and responsible artificial intelligence, combining areas such as reinforcement learning, social and cognitive computational modelling, knowledge representation and reasoning, agent-based modelling. More
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intelligent, agentic networks—combining causal inference, conformal prediction, and agent-environment modeling—to ensure trustworthy decision support and debugging of autonomous control systems? The PhD will
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. Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. In CoRR, abs/2311.16452, 2023. [33] S. Lamsiyah, A. El Mahdaouy. A Reinforcement Learning-based Method
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modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning). Experience in annotation software such as ELAN and PRAAT. Existing peer-reviewed journal publications and conference
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the features of CF networking. Thus, this position will develop a set of novel AI-based solutions for the optimization of the CF-based RAN system by applying a combination of model-based and data-driven
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. Being independent and able to interface with multiple work groups is critical. We use biochemical, proteomic, cell biology, molecular biology, genomic, epigenomic, and mouse model approaches and