WIAS invites in the Research Group
“Nonsmooth Variational Problems and Operator Equations”
(Head: Prof. Dr. M. Hintermüller) applications for a
Research Assistant Position (f/m/d)
for data-driven and variational regularization methods for dynamic image reconstruction
(Ref. 22/33)
to be filled at the earliest possible date. The position is associated to the MATH+ Cluster of Excellence EF3-12 project “Integrated Learning and Variational Methods for Quantitative
Dynamic Imaging” a joint interdisciplinary project of the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) and the Physikalisch-Technische Bundesanstalt Institute Berlin (PTB).
The work tasks include:
· Develop, analyze and implement a spatio-temporal regularization parameter learning framework for dynamic image reconstruction with a particular focus on dynamic magnetic resonance imaging (MRI)
· Develop a machine learning framework for learning the physical law processes that govern a MRI experiment and use this to enhance existing and develop new numerical algorithms for quantitative MRI
· Transfer and evaluate the developed methods to clinical application level along with the project partners
We are looking for: A motivated, outstanding researcher with a very good degree and excellent doctorate in mathematics as well as previous experience in the fields mentioned above.
Additionally, it is highly desired that the candidate has experience in:
· Mathematical imaging, in particular variational as well as data-driven regularization methods for image reconstruction
· Optimization and optimal control with partial differential equations and related numerical solution algorithms
· Scientific computing and deep learning
Technical queries should be directed to Prof. Dr. Michael Hintermüller (Michael.Hintermueller@wias-berlin.de). The position is remunerated according to TVöD Bund and is initially limited to two years.
The Institute aims to increase the proportion of women in this field, so applications from women are particularly welcome. Among equally qualified applicants, disabled candidates will be given preference.
Please upload your complete application documents, including cover letter, curriculum vitae and certificates, via our applicant portal as soon as possible but not later than October 31st, 2022 using the button “Apply online”.
We are looking forward to your application!

See here for more information: https://short.sg/j/22772235