Research Assistant / Doctoral Candidate (m/f/d) (Engineer - Construction)

At the Faculty of Environmental Sciences, Department of Geosciences, the joint project "Scots pine in climate change: climate stress, biotic risks and strategies for sustainable management" (funded by the Eva-Mayr-Stihl-Stiftung) is being carried out as part of a project consortium with three professorships. The aim of the project is to comprehensively investigate the vulnerability and adaptability of pine to drought stress and mistletoe infestation and to determine the role of genetic and phenotypic variation for its resilience in climate change. To this end, origin-related differences, growth physiological reaction patterns, and spatial stress and infestation dynamics will be recorded and evaluated.

The Technische Universität Dresden (TUD) understands diversity as a cultural self-evident truth and a quality criterion of an excellence university. Accordingly, we welcome all applicants who wish to commit themselves through their performance and personality to our success and with us.

As part of this project, a position is to be filled at the Institut für Photogrammetrie und Fernerkundung, at the Professur für Umweltfernerkundung, starting on 01.10.2026 as a

Research Assistant / Doctoral Candidate (m/f/d) (subject to meeting personal requirements E 13 TV-L)

for 48 months (employment duration according to WissZeitVG), with 65% of the regular weekly working hours. There is the opportunity for your own scientific further qualification (usually a doctorate).

Tasks:

• independent scientific research in the field of recording and analyzing spatial-temporal patterns of vitality, drought stress, and mistletoe infestation in pine forests using drone and satellite remote sensing
• development of a methodology to map mistletoe infestation and loss of vitality from satellite, aircraft, and Unmanned Aerial Vehicle UAV imagery
• planning and implementation of measurement campaigns to create training data for mistletoe infestation
• development of methods to scale results from individual trees to the landscape
• identification and analysis of the spatial relationships between drought stress and mistletoe infestation

Requirements:

• academic university degree in the field of Environmental Informatics, Remote Sensing, Geoinformatics, Geography, Geoecology, Landscape Ecology, Forest Sciences, or comparable
• demonstrable experience in the automatic processing of multi-spectral satellite or UAV data
• demonstrable experience in forest science or ecological topics
• demonstrable programming skills (e.g., Python, R)
• good knowledge of data analysis algorithms using machine learning methods
• German driving license class B
• initial experience in scientific publishing is desirable

TUD strives to increase the proportion of women and therefore expressly requests them to apply. The university is a family-friendly institution. Applications from severely disabled persons are particularly welcome. In the case of equal suitability, these or those deemed equal by law under SGB IX will be given preference.

Application: Please send your expressive application with the usual documents (including CV, a short statement on your qualifications and research interests, certificates of qualification) by 14.08.2026 (the postmark of the Central Post Office or the timestamp on the TUD e-mail server applies), preferably via the TUD SecureMail portal https://securemail.tu-dresden.de (https://securemail.tu-dresden.de/) as a single PDF document to matthias.forkel@tu-dresden.de (https://mailto:[matthias.forkel@tu-dresden.de](matthias.forkel@tu-dresden.de)) or to:

TU Dresden, Institut für Photogrammetrie und Fernerkundung, Herrn Prof. Dr. Forkel, Helmholtzstr. 10, 01069 Dresden.

Your application documents will not be returned; please only submit copies. Interview costs will not be covered.

TUD is a founding partner of the research alliance DRESDEN-concept e.V.

Note on data protection: We have provided information on which rights you have, for what purpose your data is processed, and further information on data protection on the following website: https://tu-dresden.de/karriere/datenschutzhinweis (https://tu-dresden.de/karriere/datenschutzhinweis).

Supplementary information: Requirements for the applicant: Advanced knowledge: Environmental Sciences, Research, Development, Geography, Geoinformatics, Geoecology, Remote Sensing, Programming, Forest Sciences