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and enhance grid resilience. This project aims to develop optimal coordination and control strategies for microgrids to achieve self-balancing when they are disconnected from the grids, and grid support
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feedstocks. ACCELERATE gathers leading academics and industries that want join forces. Within this effort, this position will focus on the engineering, analysis, and optimization of catalytic reactors
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of hyperdimensional computing and vector symbolic architectures (VSA). As a Senior Research Engineer, you will: Implement, optimize, and run simulation code in Matlab and Python. Develop lab assignments for upcoming
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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, including finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks
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computing, with a focus on performance analysis, development, and optimization of scientific simulation codes. The work involves applications in plasma physics, computational fluid dynamics, and molecular
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mathematics, such as extreme value theory, inference for stochastic processes, optimization theory, and/or Monte Carlo simulations. Experience in obtaining research grants in national and/or international
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candidate will work fulltime on the above-outlined research project. It is expected that they will actively and creatively develop and optimize the detailed methods to pursue the overall project goals and
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material