Postdoctoral Researcher (f/m/x) in Predictive Avifauna Modelling

The UFZ

The Helmholtz Centre for Environmental Research (UFZ) with its 1,100 employees has gained an excellent reputation as an international competence centre for environmental sciences. We are part of the largest scientific organisation in Germany, the Helmholtz association. Our mission: Our research seeks to find a balance between social development and the long-term protection of our natural resources.

The job

The newly established research group BirdFutures is seeking a creative and highly skilled Ecological Modeler to build the quantitative foundation of our project. This project’s mission is to develop cutting-edge bird diversity models and scenarios across Europe. Your work will help directly generate products for societal, business, and financial decision-making, and inform critical policy like the EU Nature Restoration Law. This is a unique opportunity to join a team at its inception that will define the future of predictive biodiversity conservation science in Europe. A core scientific challenge of BirdFuture is the integration of diverse, multi-scale datasets. The project will be fueled by fine-scale, high-resolution bird monitoring data from key partners like the Dachverband Deutscher Avifaunisten (DDA), which must be harmonized with broader, continental-scale environmental data streams (e.g., climate projections, remote sensing land cover). Success in this role will require not just technical skill, but a deep appreciation for spatial ecology and the ability to think and model across scales — from the local habitat that drives an individual bird's presence to the continental forces that shape entire populations.

Your tasks

• Working in close collaboration with the group leader and partners from the TripleBird initiative, you will co-develop innovative biodiversity forecasting models.
• Your work will form the scientific engine of the BirdFutures project. Develop dynamic (i.e., time-explicit) habitat use models to forecast the impacts of diverse policy and management options on avifauna.
• Project bird metrics with future scenarios that clearly illustrate the long-term consequences of different courses of action for decision-makers.
• Build and implement a continuous evaluation pipeline for biodiversity protection measures, using annually updated data from schemes like PECBMS.
• Play a key role, in close collaboration with other project partners, in the co-conceptualization and design of related user-friendly data products.
• Together with the team lead and the team’s social scientist, you will be responsible for translating complex model outputs into actionable insights for a diverse range of stakeholders (finance, business, conservation NGOs).
• Publish high-impact research and present your work at international conferences.

We offer

• The freedom to master even the most demanding challenges between basic research and practical application
• The chance to work in interdisciplinary, international teams and benefit from a variety of perspectives
• Firstclass integration into national and international research networks to work together on global challenges
• Excellent research infrastructure and research data management to optimally support your work
• Flexible working hours and a wide range of options for balancing work and care responsibilities through our family office
• Competent support and advice for international colleagues arriving at the UFZ from the 'International Office'
• Special annual payment, capital-forming benefits and subsidised Germany Job Ticket
• A workplace in a vibrant region with a high life quality and social and cultural diversity

Your profile

• PhD in Quantitative Ecology, Computational Biology, Biogeography, Statistics, Applied System Science or a related field.
• Strong background in developing models and scenarios of species distribution and diversity (e.g., species distribution models, occupancy-detection models).
• Excellent conceptual and quantitative skills, with high proficiency in R. Knowledge of python is an asset.
• Proficiency with GIS software and spatial analysis is essential.
• Proven experience with FAIR science principles, including reproducible workflows and version control (e.g., Git/GitHub). Experience or a strong interest and facility in using High-Performance Computing (HPC) environments.
• Strong interest in developing hybrid models that integrate mechanistic and data-driven approaches.
• Experience with diverse biodiversity data sets and heterogeneous data.
• Experience with machine learning approaches (e.g. neural networks) is an asset.
• Excellent English language skills; German and other European languages are an asset.
• A collaborative spirit and a passion for working in a deeply interdisciplinary team.

Please note that external consultants will also be involved in the selection process for this position alongside UFZ employees.