Post doc: Data integration for biodiversity dynamics - Vacancy at Aarhus University

Job description

We are seeking a highly motivated postdoctoral researcher to explore one of the most pressing scientific challenges of our time: understanding how biodiversity is changing in response to multiple, interacting global change drivers. The project will combine cutting-edge analyses of large biodiversity datasets with the integration of diverse geospatial and remote sensing data sources to quantify environmental stressors and their impacts on ecosystems. This position offers a unique opportunity to contribute to high-impact research at the forefront of biodiversity science and global change ecology.

You will work on combining extensive biodiversity datasets, innovative geospatial products, and remotely sensed observations to generate new insights into the causes and consequences of biodiversity change in Denmark and Europe. The position provides an exciting opportunity to contribute to internationally leading research, collaborate with an interdisciplinary team, and develop novel approaches for understanding and predicting biodiversity futures in a rapidly changing world.

Qualifications

Ideally, you hold a PhD in biology, earth system or data science, or a similar field, and have several years of experience with interdisciplinary collaborations focused on understanding biodiversity dynamics by integrating ecological and environmental data and knowledge across scales. 

Specifically, we look for the following qualifications:

• Proven expertise in modelling and analyses of biodiversity dynamics across large spatial and temporal scales. 
• Experience in the conceptualisation and development of new methodological approaches for analysing and modelling species range dynamics, functional trait variation, or species interactions. 
• Proven skills in integration and utilizing various remotely sensed products across scales, including both spectral and structural data streams. 
• Strong documented skills in advanced statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition.
• Proven capability to acquire, download, manage, and synthesise large geospatial datasets from diverse sources.
• Proven ability to publish at a high international level. Excellent written and oral communication skills in English are required.
• Strong interpersonal and collaborative skills, with a demonstrated ability to work effectively across disciplines and employee groups. 

At the centres, we value a collegial and inclusive working environment and place strong emphasis on good relationships between colleagues and students. We therefore seek candidates with an open, constructive, and collaborative approach.

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