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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. You will contribute to method development, simulation and
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closely with data scientists to interpret and predict MFA data using nonlinear reaction-diffusion models, 13C-isotopomer analysis, and MATLAB-based simulations enhanced by Bayesian Machine Learning
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