Environmental Data Analyst with LiDAR and AI Expertise

3 hours ago


Århus, Århus Kommune, Denmark Aarhus Universitet Full time

Aarhus University's Department of Ecoscience invites applications for a tenure track researcher or senior researcher position focusing on remote sensing and vegetation structure analysis.

Job Description:

The successful candidate will be part of the Section for Biodiversity, contributing to research and advisory work in the field of remote sensing, LiDAR data analysis, and artificial intelligence.

  • Strengthen the department's analytical capabilities by developing tools for Digital Nature Monitoring.
  • Collaborate with ongoing remote sensing activities and contribute to the development of next-generation biodiversity monitoring tools.

This role requires a strong background in programming, particularly in Python, R, and GIS. Experience with deep learning and point cloud calculations is highly desirable.

The ideal candidate should have a broad publication record covering topics such as remote sensing, LiDAR point cloud analysis, GIS applications, and vegetation structure analysis. A certain knowledge of Danish is an advantage due to communication requirements with Danish authorities.

Requirements:
  • PhD degree and established track record of publications in international journals.
  • Broad publication record covering remote sensing, LiDAR, and GIS applications.
  • Extensive experience in programming, particularly in Python, R, and GIS.

The successful candidate will be part of a dynamic team conducting applied research and advisory work for authorities. The Department of Ecoscience offers a well-developed research infrastructure, access to shared technical equipment, and opportunities for interdisciplinary collaboration.

What We Offer:
  • A well-developed research infrastructure and access to shared technical equipment.
  • An exciting interdisciplinary environment with national and international collaborators.
  • A research climate encouraging lively discussion and critical thinking.


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