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research into control theory of neural population dynamics. This position has the specific focus of developing ML methods to assess the feedback controllability of neural population dynamics recorded from
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theory & experiment: Co‑design validation experiments with experimentalists; iterate models using feedback from new measurements. Automate the workflow: Build Python workflows for simulation and data
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Qualifications: Experience in one or more of the following areas: quantum sensing, theory development aimed at experimental searches for new physics, and foundational knowledge of particle physics. The posting
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field. Demonstrated ability to perform research that addresses fundamental science questions. Demonstrated experience with computational chemistry methods including density functional theory, molecular