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or integrating control algorithms into physical testbeds Knowledge of predictive maintenance methods and anomaly detection techniques for complex systems Experience with sensor networks, IoT platforms, or real
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incorporated into complex microelectronic and optoelectronic architectures, with particular emphasis on interfaces between two-dimensional and conventional semiconductor materials. This position resides in
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of complex biosystems. The successful candidate will also contribute to efforts that bridge molecular, cellular, and systems-level modeling, with growing relevance to emerging paradigms such as whole-cell
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systems. Research activities will address key challenges in AI for science, including surrogate modeling, uncertainty quantification, and multi-fidelity optimization for complex simulation workflows
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complex magnets via interpretable machine-learning models, and develop improved AI models that can accelerate prediction of new synthesizable magnet candidates with high energy density and critical