PostDoc - Uncertainty-Aware Optimization in Inverse Problems for Next-Generation 3D Scanning

Opportunity summary

3Shape and DTU Compute (Department of Applied Mathematics and Computer Science at the Technical University of Denmark) invite applications for an Industrial Postdoctoral position partially funded by Innovation Fund Denmark. The position is a 2-year fixed-term appointment starting in January 2027 (small variations in the start date may be possible depending on the candidate’s preference). The project addresses a fundamental challenge in computational imaging and large-scale optimization: how can uncertainty in measurements be quantified, propagated, and ultimately leveraged to improve the reliability of reconstructed 3d models? Modern 3D scanning systems rely on advanced optimization algorithms to reconstruct geometry and color from large volumes of sensor data. While these algorithms produce highly accurate results, they typically provide limited information about the confidence and uncertainty associated with the reconstructed output. Developing methods that can efficiently estimate and propagate uncertainty in the input data through large-scale iterative optimization algorithms has the potential to improve reconstruction quality, enable more informed algorithmic decisions, and support the next generation of intelligent scanning systems1 …

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