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Field
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learning analytics, with a focus on the deployment of eye-trackers or fNIRS devices; creating end-to-end prototypes of AI systems, including LLM integration, backend development, and interface design and
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intelligent transportation systems (ITS), with an emphasis on developing and deploying state-of-the-art Large-Language Models (LLMs), Vision-Language Models (VLMs), and Vision-Language-Action (VLA) models
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the feasibility of prototyping an LLM-driven interactive GUI that auto-configures key inputs (e.g., Slater parameters), enabling a closed loop from model setup to analysis for accelerated studies of new materials
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Qualifications: Experience with multimodal AI, large language models (LLMs), or retrieval-augmented systems Familiarity with high-performance computing (HPC) and distributed training environments Experience with
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/ exposure to tensor network methods or and/or AI/LLM for physics would be a positive addition. For this postdoctoral position, we intend to focus on topological two-dimensional materials, flat bands, and
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developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
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and alignment of large language models (LLMs). In the last few years, LLMs found wide adoption in many areas of societal life. Their development, however, requires access to a vast amount of data and
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the integration of AI components transforms the nature of software systems (SE4AI). From an architectural perspective, the research investigates how the inclusion of AI elements—such as retrainable ML models, LLMs
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and take a lead in the group’s “Improving the quality of Translation/Revision/PEMT output by using automatic speech tools and LLMs” and “Cognitive investigations of Translation/Revision/PEMT practices
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online support platforms (e.g., 7Cups), we are developing prototypes that use LLM and conversational agents to deliver scalable, experiential micro-skills training (such as empathy, active listening, and