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Field
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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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such as graph-based approaches and network analytics to predict how blue network dynamics, fragmentation and surrounding land use interact to shape ecosystem functioning and human wellbeing outcomes
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. Applicants with training in quantitative and empirical research and experience in requirements engineering, safety-critical systems, or AI/ML/LLMs/Knowledge Graphs are especially encouraged to apply. This PhD
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the connections between clouds and climate. Ultimately, we want to create to causal graphs for large-scale cloudiness, its dependence, and its effect on the related environmental factors. Additional or alternative
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graph, and discrete random processes. The aim of this project is for the student to develop an understanding of these tools and to apply these techniques to open research problems in the field. Entry
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including: * Algorithmic game theory * Approximation algorithms * Automata and formal languages * Combinatorics and graph algorithms * Computational complexity * Logic and games * Online and dynamic
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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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sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued
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families (e.g., generative models or graph/equivariant neural networks) to accelerate candidate discovery and hypothesis generation. Disseminate research findings through publications, conference
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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