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chitosan. You will work with academic, clinical, and industrial partners in Denmark and abroad. Your primary tasks will be to: Develop and optimize flexible piezoelectric thin films and device stacks with
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learning, statistical analysis, and other contemporary data-driven techniques. Computational methods such as optimization, filtering algorithms, predictors, etc. Software and coding skills with, e.g., Python
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optimizing enzymes for diverse industrial applications. Make a tangible impact on the future of sustainable technology! These two PhD scholarships are part of a 5-year project, which also includes a
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: Machine learning techniques, statistics, and probabilities Numerical methods for time-domain simulations Power system dynamics Power system optimization Programming tools such as Python, Julia, Pytorch, etc
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to identify attacks on the power grid Leverage control and optimization techniques to mitigate the risk of cyber-physical attacks Perform benchmarks against state-of-the-art methods Qualifications : We seek
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: Machine learning techniques, statistics, and probabilities Numerical methods for time-domain simulations Power system dynamics Power system optimization Programming tools such as Python, Julia, Pytorch, etc
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intelligence and machine learning will play a crucial role in the modeling and control of these RPPs, ensuring optimized performance and efficiency. You will be part of a joint alliance research project called