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complex or high-dimensional systems. Experience with physics-informed or constraint-based machine learning (e.g. neural ODEs, energy-based models) Experience with dynamical systems, stochastic processes
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. Simulation-based inference (SBI) addresses this by training neural networks, such as flow-matching generative models, on simulated events. The project aims to develop efficient, robust and calibrated SBI
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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier and be due to circumstances such as sick leave, parental leave, duties in labor