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techniques. Knowledge of quantum computing algorithms would be a huge benefit, as would knowledge of methods to model noise in qubit systems. The person should be willing to learn to evaluating physical
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; - use the TOOCAN Lagrangian tracking algorithm, applied to these model outputs, to analyze the evolution of cloud structures and balance terms during system development; - explore the extreme values
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particular focus will be the development and benchmarking of AI- or ML-based clustering algorithms, as well as their integration for heterogeneous architectures, such as GPUs and FPGAs. If interested to do so
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clustering algorithms, as well as their integration for heterogeneous architectures, such as GPUs and FPGAs. If interested to do so, the successful candidates may also participate in physics analyses with a