PhD position in Remote Sensing for the Monitoring of Forest Resources

PhD position in Remote Sensing for the Monitoring of Forest Resources

The chair of Forest Resources Management (FORM) , led by Prof. Dr Verena C. Griess, is opening a PhD positionin Remote Sensing for the Monitoring
of Forest Resources (100%).

The desired starting date is January 1st, 2023. A different starting date can be negotiated.

Forests provide numerous ecological, economic, and climatic benefits, yet they are highly vulnerable to climatic extremes. Active management of forest ecosystems for resilience and adaptation is crucial to ensure that forests can continue to provide these benefits. Forest monitoring - in particular tree species identification - is a fundamental building block to achieving these goals and enabling sustainable forest management.

With the aim of developing the first automatic tree species detection model of its kind that can be applied across forest types, this multidisciplinary project will combine open-source aerial imagery, ground-truth data and terrestrial lidar data from Swiss-, European, and Global forests, with various deep learning methods. The automatic species detection will serve as a basis for improved inventory planning, for the planning of forest operations, and to ensure targeted management activities for more resilient forests.

To achieve this goal, we will:

• develop Convolutional Neural Network (CNN) based -object detection (e.g., Faster R-CNN, YOLO, or SDD) and -instance segmentation (Mask R-CNN) approaches to detect trees species from the overstory in remotely sensed imagery;
• assess the transferability of these models to different forest types across Europe; and
• evaluate the capabilities of terrestrial lidar to detect saplings from the understory, and developing standard workflows for doing so

• In close collaboration with the FORM team you will work towards a doctoral thesis, which will comprise the project steps described above.
• You will contribute to, and participate in the various activities of the group, including related research and teaching activities.
• You will collect data at our field sites within Switzerland on a regular basis, using a drone and/ or terrestrial lidar equipment (no previous experience required), and will interact with forest practitioners and scientists working on similar topics.
• You will join an inclusive and supportive working environment that praises scientific curiosity and creativity.

• You are highly motivated, committed and creative.
• You can work in a multidisciplinary team and have great communication skills.
• At the time of appointment, you have finished your University level Master’s degree in Environmental Sciences (Major Forest and Landscape Management), Forest Sciences, Geoinformatics, or a closely related field.
• Good English skills are essential and German communication skills are desirable.
• A good command of programming languages such as Python and/or R and knowledge of GIS tools are preferred, or an explicit willingness to learn has to be shown.
• Experience in processing LiDAR data is of advantage for an application.

ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.

Your complete application consists of the following:

• Cover letter, no more than 2 pages in length, describing:
  • reasons for pursuing a doctorate in Forest Resources Management at ETH Zurich
  • your motivation to apply for this specific posting,
  • a short description that separately and clearly addresses how you possess each of the qualifications listed above
• Detailed CV, including a publication list (if applicable)
• Degree certificates and transcripts (BSc, MSc, and any other degrees you may hold)
• Names and contact details of 2-3 references

The position is open until filled. 

All documents must be in PDF format. Please note that we exclusively accept applications submitted through our online application portal.

For further information, please, contact Ms Ariane Hangartner; [email protected]  (no applications by e-mail) or visit our website .