PhD position (m/f/d) Remote sensing of mountain forests dynamics

PhD position (m/f/d) Remote sensing of mountain forests dynamics

PhD position (m/f/d) Remote sensing of mountain forests dynamics

PhD position (m/f/d) Remote sensing of mountain forests dynamics

Technische Universität München

Fach- und Hochschulen

München

  • Art der Anstellung: Vollzeit
  • 48.500 € – 70.500 € (von XING geschätzt)
  • Hybrid
  • Zu den Ersten gehören

PhD position (m/f/d) Remote sensing of mountain forests dynamics

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PhD position (m/f/d) Remote sensing of mountain forests dynamics

04.09.2025, Wissenschaftliches Personal

Funded by the Eva Mayr-Stihl Foundation, a new Centre for Forest Management in the Alps will be installed at the TUM School of Life Sciences. Within this centre, we are opening a PhD position on remote sensing of mountain forest dynamics.

The Technical University of Munich (TUM) is one of the leading universities globally. At the TUM School of Life Sciences one focus is on forest ecosystems, aiming to better understand their dynamics and contributing to their sustainable management. Funded by the Eva Mayr-Stihl Foundation, a new Centre for Forest Management in the Alps will be installed at the TUM School of Life Sciences. The goal of the new centre is to bring together different disciplines and perspectives to further the sustainable management of mountain forests in the Alps. The current position will be part of the Centre for Forest Management in the Alps, and will work in the subproject 4, remote sensing of mountain forest dynamics (Prof. Dr. Cornelius Senf).

Your profile
We are looking to fill the position of a PhD student (m/f/d) in the field of remote sensing (TVL13, 75%), available from January 2026 for 42 months. Your profile should include:

  • Completed master studies in the field of environmental sciences, forestry, landscape ecology, remote sensing or related fields
  • Interested in remote sensing, quantitative methods and programming
  • Prior experience in remote sensing and programming is a plus (e.g., using QGIS or R)
  • Good communication skills
  • Ability to work in a team

Your tasks
You will conduct research on the use of remote sensing data for upscaling mountain forest ecosystem proper-ties (e.g., productivity, phenology) from in-situ data to the landscape scale. Doing so, you will address questions of climate change and disturbance impacts on mountain forest dynamics, and how these can be moni-tored from remote sensing data. Specifically, tasks include:
  • Processing and analysis of remote sensing data
  • Combining remote sensing and field data for upscaling ecosystem properties (e.g., productivity, phenology)
  • Contribute to the development of an Alpine remote sensing monitoring system
  • Interactive collaboration and exchange within the TUM Center for Forest Management in the Alps
  • Publication of peer-reviewed scientific papers in international journals
  • Communication of research findings at scientific conferences and stakeholder meeting

Our offer
  • Work in a highly dynamic and international research group at the forefront of the field
  • Embedded into a newly established, interdisciplinary research centre with focus on mountain forests
  • Interact with a wide network of peers, scientists and stakeholders both nationally and internationally
  • 75% position (30h employment per week) in remuneration group TV-L E13, for a period of 42 months
  • The place of employment is the TUM School of Life Science in Freising, Germany
  • Severely handicapped persons will be given preference in case of essentially equal qualification
  • The TUM aims to increase the proportion of women in its staff; applications from women are therefore expressly welcomed

Contact
Please send your digital application, consisting of a complete CV and a concise motivation letter, as one PDF named "lastname_firstname.pdf” by September 21st, 2025, at the latest to: cornelius.senf@tum.de For questions about the position, please contact Prof. Dr. Cornelius Senf, cornelius.senf@tum.de. As part of your application for a position at the Technical University of Munich (TUM), you will be submitting personal data. Please refer to our data protection information in accordance with Art. 13 of the General Data Protection Regulation (DSGVO) https://portal.mytum.de/kompass/datenschutz/Bewerbung/ regarding the col-lection and processing of personal data as part of your application. By submitting your application, you confirm that you have taken note of TUM's data protection information.
Find out more about us at https://www.lss.ls.tum.de/eoem/

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Kontakt: cornelius.senf@tum.de

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