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inference pipelines for soft biomechanical systems, including differentiable physics engines, to support interpretable analysis, parameter estimation, sensitivity studies and uncertainty quantification. By
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architectures (e.g. neural ODEs, flow matching and continuous normalising flows), robustness, interpretability and uncertainty quantification; collaborate with researchers across the ACT to identify emerging
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, analyse, and validate innovative numerical algorithms and mathematical frameworks for problems arising in materials, fundamental physics, dynamics, optimisation, control, uncertainty quantification, inverse
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trustworthiness: developing and validating trustworthy AI methods for space applications, with emphasis on explainability, robustness, uncertainty quantification, safety assurance and compliance with relevant