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Field
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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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federated knowledge graph framework that facilitates the querying, consolidation, analysis, and interpretation of distributed proteomics-focused clinical knowledge graphs. To achieve this, we will employ
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to the architecture and technical design of the VIOLET research prototype Design and develop AI systems for guideline-compliant therapy recommendations using LLM, RAG and/or graph paradigms Translate narrative clinical
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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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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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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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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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be developing advanced spatial models such as graph-based approaches and network analytics to predict how blue network dynamics, fragmentation and surrounding land use interact to shape ecosystem
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learnable physical kernels, geometry encodings, and boundary-aware layers; compare to PINNs, U-Nets, graph operators, and transformer baselines. Learning strategy: physics-informed and multi-task losses