The main responsibility for the candidate is to assist in the development of efficient algorithms for statistical analysis of DNA samples and participate in an interdisciplinary research project with Dr. Lars Ruthotto as well as his collaborators Dr. Vigfusson and the Simbiosys lab. The project is funded by the Center for Disease Control (CDC) and includes statistical modeling, parameter estimation, mixed-integer optimization, and uncertainty quantification. In addition, the postdoc is expected to conduct individual research, complement other ongoing projects in the group (e.g., in image registration, machine learning, PDE parameter estimation) or both. 

The successful candidate has a doctoral degree in Mathematics, Engineering Computer Science, or a related subject, has strong programming skills (preferably MATLAB, Julia, or Python), and ideally has strong expertise in one or more of the following areas:
- Inverse Problems, particularly, Bayesian computing and uncertainty quantification
- Numerical Optimization, particularly, mixed-integer optimization and optimal control
- Numerical Partial Differential Equations, particularly, model order reduction, multiscale methods
- Machine Learning, particularly, in deep learning

Interested candidates should contact Lars Ruthotto at This email address is being protected from spambots. You need JavaScript enabled to view it..

Review of applications will begin immediately and continue until the position is filled. The position is available immediately, however, the start date is flexible.
Contact: This email address is being protected from spambots. You need JavaScript enabled to view it.