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AI-driven tools for bio-retrosynthesis-based metabolic pathway design, enzyme design and optimization, and DNA part selection. 2) knowledge-graph-based combinatorial experiment designs are used to span
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the response model from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques
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., symmetries), learning on structured domains (e.g., graphs, manifolds) (to achieve data efficiency and respect constraints) Uncertainty Quantification: building models that quantify uncertainty associated with
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), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued. Mathematical skills: Competence in mathematical modeling of dynamic systems and
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methods for data assimilation; and graph-based multi-scale neural network models. While the developed methods will be broadly applicable, particular emphasis will be put on the problem of inferring gas
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knowledge-graph groundedfactuality in LLM. The PhD students will work both independently and collaboratively within the group, and will have opportunities to engage with national and international partners