Job ad: Postdoc in Mathematical Analysis and Statistical Learning for Uncertainty Quantification for Inverse Problems at DTU Compute

Postdoc in Mathematical Analysis and Statistical Learning for Uncertainty Quantification for Inverse Problems at DTU Compute

Do you want to work in an interdisciplinary research team and contribute to the development of and methods for uncertainty quantification (UQ) for inverse problems? We invite applications for a two-year postdoc with focus on the development of mathematical and statistical theory that guides and brings insight to computational methods for UQ.

This position focuses on the development and use of statistical learning as a framework for formulating and performing computational UQ. You will be responsible for advancing the mathematical and statistical theory behind UQ for inverse problems, e.g., arising from partial differential equations. In addition, you will together with the team aim for bridging the gap between rigorous theoretical analysis and computations.