• research within the BMBF Projekt Verbundprojekt 05M2026 - IPI: individualisierte Patientenmodelle in der lntensivmedizin.
• subproject 2: Generative models for Bayesian parameter identification in cardiovascular models

Further information can be obtained from Prof. Dr. Gabriele Steidl (steidl@math.tu-berlin.de).

• successfully completed sientific university degree (master's degree, diploma or equivalent) in mathematics or computer science/engineering with in-depth knowledge of analysis, optimisation, stochastics and the implementation of (generative) neural networks
• knowledge of (medical) image processing
• good knowledge of German and/or English required; willingness to acquire the respective missing language skills (because of cooperation in the medical field)
• enjoy working in a team (is desired)

Please send your application with the reference number and the usual documents by email (in a single pdf file, max 5 MB) to steidl@math.tu-berlin.de.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ .

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.