The chair of Forest Resources Management (FORM) is seeking a motivated student to assist in developing Deep Learning approaches for tree species identification. This project focuses on mapping individual trees and quantifying their species, which are critical tasks for forestry management. Using aerial RGB imagery, we aim to create a cost-effective, automated system for detecting and identifying tree species, with broad applications in forest monitoring. In collaboration with colleagues from Austria, the successful approach will be implemented in a protected area in Austria, with the goal of quantifying tree species diversity.
You will contribute to a project focused on automating the detection of individual tree species in forests using deep learning. Specifically, you will:
1. Apply deep learning techniques in Python to process spatial and aerial data.
2. Integrate datasets such as tree species annotations, climate, and topography into deep learning algorithms.
3. Test deep learning models (Transformers and CNNs) for optimal accuracy using large datasets, including over 11,000 tree species annotations from Switzerland, along with climatic, topographic, and lidar data.
4. Evaluate the best algorithm for identifying tree species in a protected area in Austria using the most accurate deep learning model.
Profile
1. You are a student enrolled at ETH or a Swiss university, ideally in Geoinformatics, Machine Learning, Environmental Sciences, or a related field.
2. Proficiency in Python programming is essential.
3. Knowledge of GIS tools (QGIS or ArcGIS).
4. Experience working with spatial data, shapefiles, raster data is required.
5. Experience with lidar data processing is a plus.
6. You are available for 15 hours per week starting 1 July 2025 for 2-3 months.
Workplace
We offer
1. A valuable learning opportunity through a concrete project.
2. Involvement in cutting-edge technology and research.
3. Potential for publication of results.
4. Flexible and remote working hours.
5. A workspace in the CHN building.
The position is remunerated at CHF 30.70 per hour, starting in July 2025. Applications received by June 22nd will be given full consideration. The position remains open until filled.
ETH Zurich promotes an inclusive culture, valuing diversity and ensuring a respectful environment for all staff and students. Visit our Equal Opportunities and Diversity website for more information.
Interested? We look forward to your application.
Please submit your application online with:
* Your CV
* Your transcript of records
Applications via email are not accepted. For further information, visit our website. Questions can be directed to Mirela Beloiu Schwenke or Ariane Hangartner via email at mirela.beloiu(at)usys.ethz.ch or ariane.hangartner(at)usys.ethz.ch.
ETH Zurich is a leading university in science and technology, known for excellent education, research, and societal impact. Located in Europe, it fosters global connections to address major challenges.
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