Postdoc (TV-L 13, 100%) in tree-ring research / forward modelling
The ERC project MONOSTAR seeks to explore tree growth at multiple sites across the Northern Hemisphere and develop forward models to explain non-stationary growth responses at regional to continental scales. The postdoc will coordinate a hemispheric network of highresolution monitoring sites, run and develop tree growth forward models, and apply model-data fusion techniques to evaluate and explain 20th century growth divergence.
We offer you an exciting research atmosphere in a vibrant international team of interdisciplinary dendrochronologists and climatologists aiming towards an improved understanding of tree growth dynamics over the past decades to centuries. We provide access to a state-of-the-art tree-ring laboratory including radiodensitometric and wood anatomical facilities, participation as a teacher in our bachelor and master programs, and support for conducting and disseminating scientific research in international journals.
The deadline for applications is March 10th, 2021. Later applications will be considered until the position is filled. Please send your application including a CV and certifications as a single PDF to Heike Zimmer-Zachmann (email@example.com). Applicants are asked to specify their desired starting date and provide contact details of 1-2 academic referees. In case of questions, please contact Prof. Dr. Jan Esper (firstname.lastname@example.org). The Johannes Gutenberg University is committed to increase the proportion of women in research and therefore encourages female scientists to apply. Applicants with disabilities will be preferentially considered if equally qualified.
We are searching for a highly motivated and creative postdoc ready to conduct field work in Northern Hemisphere tree-line environments and capable of analyzing larger scale dendrochronological networks. The ideal candidate already gained knowledge in the parametrization and application of forward models or has the analytical skills to learn and apply such techniques at the interface to empirical data. A PhD in geography, forestry, environmental sciences or related field is required.