What we do

We connect methodological developments in data science with application-oriented research questions from the environmental, ecosystem, and forest sciences.

About the Environmental Data Science Section

Data-driven methods and AI applications are advancing rapidly in the environmental, ecosystem, and forest sciences and are becoming a central component of research. At the same time, solid data science and AI skills are gaining importance for students in these fields — for academic careers as well as for entering the job market outside academia.

“A bridge between data-driven methodological foundations and concrete environmental and forestry applications.”

The particular added value of the section lies in the systematic combination of methodological developments in data science with application-oriented research questions from the forest and environmental sciences. In doing so, it serves both as a network and as a thematic platform for application-oriented research.

What are our goals

1. Coordinating and connecting research activities in data-driven environmental and forest research.
2. Promoting cross-faculty collaborations between application and methods disciplines.
3. Supporting joint third-party funding applications, particularly in interdisciplinary collaborative projects.
4. A framework for joint theses and doctoral projects across faculty boundaries.
5. A point of contact for doctoral researchers at this interface — for exchange, co-supervision, and colloquia.
6. Workshops and seminars.
7. Developing cross-faculty elective modules and teaching formats in the field of environmental data science.

Courses

Theses

What is being planned?

Do you conduct research at this interface?

The Environmental Data Science Section welcomes new collaborations from the environmental, ecosystem, and forest sciences as well as related methods disciplines. Please contact the section speaker, Dr. Nils Nölke (Nils.Noelke@forst.uni-goettingen.de), directly.