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(based on stochastic optimization), develop scenarios of the energy transition, conduct policy analyses and technology evaluation. The insights will be published in leading international outlets and
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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
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learning - deep neural network, recurrent neural network, LSTM Optimization theory Stochastic geometry Strong programming skills in at least one of the following: MATLAB, Python, JULIA or C++. Highly
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