Birth simulation via machine learning- Funded PhD position (65%) TV-H (Pay grade E 13)

The recently funded Leibniz Collaborative Excellence project entitled, “Paleo-obstetrics Understanding via Simulation and Heuristic Artificial Intelligence Tools” (PUSH@IT) is a joint venture of the Senckenberg Gesellschaft für Naturforschung (SGN) and several international institutions including Goethe-University Frankfurt/Main, the University of Zürich, Duke University and Aix-Marseille University. It involves a network of clinical and academic researchers interested in applying their respective expertise to understanding the unique human birth process and its evolutionary significance.

PUSH@IT is based out of the division of Paleoanthropology at the Senckenberg Research institute and Natural History Museum Frankfurt where we invite applications for a PhD student interested in contributing to research on birth difficulty via machine learning and finite element simulation. The position will be formally held through the SGN. The PhD student will be enrolled as a doctoral student at the Goethe-University Frankfurt/Main via the faculty of Biological Sciences.

You can find more out more information about the position via the provided application link. Application materials should be submitted to recruiting@senckenberg.de by July 1st, 2023. Questions regarding scientific aspects of the position can be directed at the project leader, Dr. Nicole Webb, at nicole.webb@senckenberg.de