25 postdoc-finite-element-microstructure Postdoctoral positions at Leibniz in Germany
Sort by
Refine Your Search
-
combination with methods of nonlinear spectroscopy. With its research, MBI fulfills a national mission and is an integral part of the international scientific community. MBI invites applications for PostDoc (m
-
(a limited liability company) with a non-profit character and one of the largest non-university institutions of its kind in Germany. We are looking for a PostDoc/Senior Researcher (f/m/d
-
look forward to receiving your application with the reference number 2025-010 BI-PostDoc until 17 August 2025 using the application form . Please note that flyouts are scheduled for September 16 and 17
-
in non-academic, participatory contexts and projects with their own citizen science component. Your tasks: For researchers (m/f/d) working on their doctorate: to develop a historical, cultural or
-
position or post-doctoral position (m/f/d) (Position number: 19-2025 Postdoc PREVENT) in the field of Weather Extremes and Climate Modelling, starting on 01.09.2025. The position is funded for 12 months
-
. PIK is offering a Postdoctoral Position as an Earth Resilience Analyst (m/f/d) (Position number: 27-2025 Postdoc ERSU) for the Earth Resilience Science Unit, starting on 01.09.2025. The position is
-
all relevant certificates, curriculum vitae, and academic history including the reference code "IP Vital PostDoc Ergo" until 30th of April 2025 preferably by mail to bewerbung(at)ifado.de . Alternative
-
access to a wide range of spatial and temporal biodiversity and environmental data and a fantastic opportunity to become part of European networks of established researchers, postdocs, and graduate
-
Economics (m/f/d) (Position number: 14-2025 Postdoc Spatial Equilibrium) in the field of spatial equilibrium modeling, starting on 01.08.2025. The position is initially funded for 18 months, with
-
missing factor in soil GHG flux models. BoTiKI aims at filling this knowledge gap and establish improved GHG models accounting for soil fauna. To achieve this, we create a rich AI-training dataset