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Field
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on classical supercomputers. Design and optimize classical simulation algorithms for quantum circuits. Explore approximate classical simulation algorithms (e.g., tensor networks, circuit cutting) to improve
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(e.g., superconducting quantum processors). Validate, analyze, and interpret experimental data and results. Simulate the performance of quantum circuits on classical supercomputers. Design and optimize
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. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing
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tasks that best suit your strengths. This could involve the design, optimization, and fabrication of advanced devices using numerical methods like FDTD; taking charge of spectroscopic experiments
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inflow reconstruction techniques for lidar-assisted control and load assessment/validation. Contribute to the development and modelling of wind turbine control methods with the aim to optimize wind turbine
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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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, -- mathematical theory for artificial intelligence, -- optimization and numerical computation over manifold, -- systems and control theory, -- algebraic computation theory and cryptography. The position is for two
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resource optimization. o Entanglement dynamics, quantum control protocols, and hybrid quantum-classical algorithms. o Modeling and benchmarking atomic qubit architectures. · Collaboration: Work closely with
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and