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Retrieval-Augmented, Multi-Modal, and Explainable LLM for Fact-Checking School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Delvin Ce Zhang Application Deadline: 30
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learning or AI models. The role also involves applying principles from human–computer interaction and assisting with augmented reality features as needed for project activities. In addition to technical
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; explainable AI; cognitive/brain-inspired computing; human-centric AI; intelligent assistants; intelligence augmentation; human-in-the-loop AI. · Human-Machine Collaborative Systems o Pervasive Sensing
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) implementation in Blender or Unity and evaluation of the case studies, v) coordination of the activities with the other project members. Where to apply Website https://www.univr.it/it/concorsi/contratti-e-assegni
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. This project combines machine-learning-augmented simulations and microfluidic engineering to explore the biomimetic design of antimicrobial nanotechnology. The engineering design will be supported with practice
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opportunities to forge synergistic collaborations with other research and education centers (https://www.birds.cornell.edu/home/about/our-work/) at the CLO as well as with relevant academic departments and
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experimental psychology and cognitive science to augment human intelligence with AI. Your experience and ambitions eligible for PhD study at Aalto University (https://into.aalto.fi/display/endoctoralsci/How
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teaching. Knowledge of ways to instruct, manage, motivate and evaluate students. Experience to draw upon their own clinical training and experience to augment their teaching in the classrooms. Ability
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, and institutional content). • Implementation of Retrieval-Augmented Generation (RAG) with semantic and geographic indexing. • Fine-tuning to improve cultural coherence, multilingual responsiveness, and
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will develop and evaluate approaches for responsible advice-giving and information retrieval systems (e.g. retrieval-augmented generation (RAG)), for instance by using interpretability techniques