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understanding (or be capable of rapidly obtaining a good understanding) of concepts from discrete mathematics in relation to graph theory, Boolean function theory and related topics. An interest in applying
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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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processing, signal processing, and network resource management to enhance performance. To optimize and analyze complex 6G networks, we use AI/ML, graph theory, and optimization techniques Furthermore, our
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theory, and machine learning to quantify and understand cancer biology. We are seeking a highly motivated Postdoctoral Researcher to develop new computational methods for the analysis and interpretation
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, graph theory, and optimization techniques Furthermore, our activities are experimentally driven and supported by the COMMLab , the 6GSPACE Lab , the CSATLab , the HybridNetLab , the QCILab , our SW
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be expressed in many different ways: for example, via logic (e.g. logical satisfiability problems), combinatorics (e.g. graph homomorphisms), or algebra (e.g. systems of equations over a field). Such
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different nationalities, backgrounds and fields. As a postdoctoral researcher, you receive benefits in career development, networking, administrative and technical support functions, along with good
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general combinatorial problems that can be expressed in many different ways: for example, via logic (e.g. logical satisfiability problems), combinatorics (e.g. graph homomorphisms), or algebra (e.g. systems
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representations in the form of ontologies, knowledge graphs, and neuro-symbolic learning, offering sound grounding also for Large Language Model (LLM) outcomes to drive knowledge-infused AI. The incorporation