Five Postdoctoral or PhD researchers in quantitative Environmental Sciences – KIT Germany 2022
About us
The positions will be held within the Land Use & Climate Change Research Group (https://landchange.imk-ifu.kit.edu/) and/or the Global Land Ecosystem Modelling Group (https://lemg.imk-ifu.kit.edu/) of the Karlsruhe Institute of Technology (KIT), located at KIT’s attractive ‘Campus Alpin’ in Garmisch-Partenkirchen, Germany. You will be welcomed into a multi‐disciplinary, highly collaborative and friendly team, well connected to national and international research networks and activities.
Your tasks
We are seeking to appoint up to 5 quantitative Environmental Scientists as either postdoctoral researchers or PhD students. The successful applicants will contribute to a number of EU-funded research projects exploring the impacts of environmental and policy change on land use and ecosystems, including biodiversity at large spatial scales (European to global). See the Annex for further details about these projects.
Specifically, we seek researchers to address the following topics:
1. The contribution of sustainable forest management to climate change mitigation, adaptation and nature conservation;
2. The nexus between biodiversity, food and timber production, climate change mitigation, water resources and health;
3. Nature-based solutions to reduce climate change risks;
4. The role of international trade and environmental policy in land use and ecosystem change.
You will contribute to the further development and application of the LandSyMM modelling framework (https://landsymm.earth/) using environmental modelling, data analysis methods and literature review. Willingness to engage with stakeholders is also expected for some of the tasks. The positions will entail contributions to project management and reporting, and some teaching.
Your profile
You will have a PhD or Master’s degree in a relevant discipline such as environmental sciences, geo-ecology, meteorology, geography, forest ecology, ecological economics, computational social sciences, mathematics and informatics. You will also have:
1) strong quantitative skills in environmental modelling and preferably computer programming experience (e.g., Fortran, C, C++, Java, Python);
2) and/or the analysis of large-scale datasets in the environmental sciences;
3) and/or experience with scenario analysis, environmental policy analysis, statistical analysis, and ecosystem assessment.
You will need to have proficiency in the English language, both spoken and in writing. Willingness to travel to interact with consortia partners is required.
Your benefits
Salaries will range from €38000 to €61000 gross per annum depending on qualifications and experience based on the Collective Agreement for the German Public Service Sector (TV-L EG13, St. 1-4). PhD students may also be funded through a stipend (studentship). The positions are available from September 2022 for 2-3 years initially with the potential for extension beyond this period.
Your application
Applications should be sent by email to Sylvia Kratz (sylvia.kratz@kit.edu) by Friday 22 April 2022, quoting the reference, 5MRAA. Applications should be submitted within a single PDF document that includes your CV, publications list (with citations), a short (1-2 page) letter of motivation and contact details for 2 referees. The motivation letter should clearly state a) your skills and experience in quantitative environmental sciences b) whether you are applying for a postdoctoral or PhD position, and c) how your research interests relate to the topics given above and the project descriptions in the annex. Please also indicate where you heard about this job opportunity. Applications that are incomplete or do not address these criteria will not be considered.
Interviews will be held remotely between Tuesday 3 May and Thursday 5 May 2022.
KIT strives to achieve gender balance at all levels of employment. We therefore particularly encourage female candidates to apply for this position. With appropriate qualifications, applications from persons with handicaps are treated preferentially.