24.09.2021, Wissenschaftliches Personal
The job will be mainly associated with the Professorship for Forest and Agroforest Systems in Freising, Germany.
The successful candidate will be focusing on recording and describing forest scenes and trees with terrestrial laser scans (3D point clouds) and analyzing stem core samples in view of increment and annual drought stress and linking these to one another.
Data will be collected in the field and analyzed in the laboratory.
Topic:
Forest structure, tree neighborhood complementarities and competition as drivers for growth and
drought stress in European beech, Douglas fir and silver fir
The candidate we are looking for ideally has:
❖ Pronounced scientific curiosity and knowledge of forest ecosystems and silviculture
❖ Enthusiasm for and competence in quantitative data analysis
❖ Experience with spatial 3D data and computing
❖ First experience modelling and relevant languages (R, Python etc.)
❖ Strong interest in further developing programming skills
❖ Interest in teaching, supervising, and working with students
Job requirements:
❖ Excellent diploma or master’s degree in a related field (forest ecology and biometry)
❖ Excellent knowledge of English
❖ Pronounced scientific and writing skills are a benefit
Starting date:
01.01.2022 (part-time 65%, fixed-term for 3 years)
Interested?
We are looking forward to receiving your comprehensive standard application documents as single
PDF file (W018_01_surname_forename.pdf)
in an email attachment to Prof. Dr. Peter Annighöfer,
[email protected]
or by postal mail to Prof. Dr. Peter Annighöfer, Hans-Carl-v.-Carlowitz-
Platz 2, 85354 Freising, Germany.
Questions regarding project or position?
Please contact: Prof. Dr. Peter Annighöfer; [email protected]
Application closing date:
31.10.2021
The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.
Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: [email protected]
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