Summary
The University of Bonn is inviting applications for 1-2 full-time doctoral researcher positions in the Laboratory for Machine Learning in Earth Observation. This initiative is part of the AI Emmy Noether Research Group focusing on developing advanced neural-field representations for Earth observation.
Doctoral Researcher Positions in Machine Learning for Earth Observation, University of Bonn, Germany
Designation
Doctoral Researcher / PhD Position
| Detail | Information |
|---|---|
| Research Area | Machine Learning, Geospatial Data Science |
| Location | University of Bonn, Bonn, Germany |
| Eligibility/Qualification | Master’s degree in relevant fields |
| Application Deadline | Open until filled; reviewed on a rolling basis |
Research Area
- Developing machine learning methods for spatial, temporal, and multimodal data including:
- Satellite imagery
- Environmental variables
- GIS layers
- Contributing to open-source research software and publishing findings in machine learning publications.
Location
University of Bonn, Germany
Eligibility/Qualification
- A very good Master’s degree in:
- Computer Science
- Geodesy
- Remote Sensing
- Machine Learning
- Data Science
- Geoinformatics
- Computational Geoscience
- Physics
- Mathematics or related fields
- Strong Python programming skills
- Experience with PyTorch or JAX
- Mathematical maturity in linear algebra, probability, and optimization
- Very good written and spoken English
- Additional experience in implicit neural representations or geospatial foundation models is advantageous.
Job Description
The successful candidate will:
- Develop machine learning methods for diverse geospatial data
- Work on creating continuous, queryable, and uncertainty-aware representations of the Earth
- Collaborate with a multidisciplinary team
- Contribute to reusable benchmarks and open-source research software
- Supervised by Marc Rußwurm with opportunities for collaboration with a broader team.
How to Apply
Interested candidates should submit their applications in English via the following link: Application Form. The application must include a single PDF (max 10 MB) containing:
- A motivational cover letter (max 2 pages) explaining your motivation for pursuing a PhD and one research question you wish to explore.
- Your detailed CV.
Last Date to Apply
Applications are open until filled, and will be reviewed on a rolling basis.
Contact Information
For more inquiries, contact:
Email: marc.russwurm@uni-bonn.de
More Information: meo-lab.com | marcrusswurm.com
