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supervised by Sebastian Throm. The subject area of the announced position covers kinetic theory, non-local diffusion and dynamics on graphs. The precise research direction will be determined together
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level or equivalent in computer science, mathematics, or a related field, corresponding to at least 240 higher education credits. Knowledge in graph theory, classical/parameterized complexity, and
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covers kinetic theory, non-local diffusion and dynamics on graphs. The precise research direction will be determined together with the successful candidate upon personal background and interests
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. Proficiency in programming languages, compilation techniques and optimizations. Proficiency in C, C++, and/or Rust. Merits: Experience with e-graphs. Familiarity with theory and algorithms used by, for example
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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. This allows us to scale up ECOCs to large lengths independently of the original number of classes. Efficient graph-based coding schemes from modern coding theory can then be designed to improve the performance
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of Technology as employer. You will be part of a lively research environment with fun interaction with researchers in the area of the position and in other areas such as type theory, graph theory, functional
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compile linear algebra expressions when the matrix sizes are unknown at compile-time. The project aims to address the problem using e-graphs. An e-graph is a data structure commonly used in automated