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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so
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accountably. This is where you come in. Your mission Working at the intersection of privacy research and real-world engineering, you'll design and build a computational stewardship engine—an autonomous agent
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collaboration, funded through the Centre for Research-based Innovation, SFI-CELECT (Research Centre for Effective Engineering and Learning in Complex Systems) . The position is 3-year doctoral research
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. The position focuses on the development of bioinspired randomly featured materials with enhanced energy absorption. As a candidate, you will establish a hybrid numerical and data-driven bioinspired design
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concerns and creative design processes. Investigate novel computational and performance-driven design workflows and their impact on creative thinking and ideation within the early stages of the architectural
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The PhD project aims to design, construct, and evolve new metabolic pathways for producing and degrading halogenated metabolites and related compounds in Pseudomonas putida . These engineered strains will
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to reach their full potential. TUD embodies a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active participation. For TUD diversity is an essential
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will be designed to work collaboratively with trainees and instructors rather than replacing them. The AI agents will leverage LLMs for knowledge acquisition, natural language interaction, and decision
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regular cross-national supervision meetings and project workshops. While the overall framework of the HEMI project will guide the doctoral research, the specific design of the PhD project will be further
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that the agent will learn from simulator data and expert knowledge, and will be designed to work collaboratively with trainees and instructors rather than replacing them. The AI agents will leverage LLMs