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Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph theoretic approaches to design quantum photonic experiments. Additionally, the position involves
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structural and algorithmic graph theory. The purpose of the role is to contribute to the project “Algorithmic meta-classifications for graph containment”, working with Professor Matthew Johnson, Dr Barnaby
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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and
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graph theory. Qualifications Candidates with a Ph.D. in any area of cognitive neuroscience broadly defined (e.g., Psychology, Neuroscience, Computer Science, or a related field) are welcome to apply
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. There will be three research fellows appointed in different stages of the project. For this post, the successful candidate will primarily focus on developing LLM agents to support effective theory of mind
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, in a large variety of fields including defence, astronomy, art investigation, or medicine. Our research activities range from signal and image processing theory to application, and impact different
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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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, collaborating across disciplines to tackle fundamental challenges through innovative methods, theory and critical analysis. The fellowship period is 3 years. Starting date as soon as possible and upon individual