PhD candidate molecular ecology (65%, d/f/m) Biodiversity of the rhizosphere and fitness of native forests in climate change

extreme drought experimental site

30.10.2022, Wissenschaftliches Personal

The group Ecophysiology of Plants at LSAI and TUM School of Life Sciences are looking for a Ph.D. student interested in relationships between the fitness of forest trees and the diversity of their rhizospheres by using multi-community DNA barcoding. Your tasks include establishing and applying novel sequencing approaches for rhizosphere community analyses and data evaluation integrating tree growth data.

Your Topic

…will be to uncover relationships between tree growth and rhizosphere biodiversity. You will investigate the biodiversity of complex rhizosphere communities and their relationship with tree growth dynamics using natural forest sites throughout Bavaria and an experimental site* for testing extreme drought. A combination of novel community sequencing approaches for root associated microorganisms, data from long-term forest monitoring, and addi-tionally collected tree growth data will uncover interrelationships between stand growth, biodiversity conservation and climate suitability of the trees and make them usable for forestry measures under changing climate. *https://doi.org/10.1002/bes2.1862

Your tasks

• analyzing forest rhizosphere communities (aiming at major taxa of fungi, bacteria, protists) and establishing oxford nanopore long read community barcoding as monitoring tool
• adjusting sequence analyses pipelines; bioinformatics
• compiling tree characteristics and long term monitoring data in co-operation with TUM chair of Forest Yield Science and the Bavarian State Institute of Forestry
• integrative analysis of rhizosphere biomes, tree characteristics, and stand level data – methods spanning the range of modern multivariate ecological statistics
• publication of project results

Your qualifications

• degree in related field (e.g., biology, ecology, forestry, microbiology, bioinformatics)
• excitement for bridging gaps between research disciplines
• ability to work on field sites, in wet- and dry-lab (processing DNA sequences)
• knowledge in ecological/statistical data analysis in R or related and enthusiasm to learn
• experience in NGS DNA-sequencing / sequence analyses in R or Python
• optimally a driving license and ability for organizing field work with German speaking partners
  

Our offer

• working on central topics of our time: trees in changing climates, biodiversity, data driven analysis
• integration in our young and multidisciplinary unit (from soil microbiology to tree physiology and modelling) within Germany’s biggest green campus (TUM School of Life Sciences in Freising)
• a broad variety of national and international co-operations, among others the Kroof Experiment (https://doi.org/10.1002/bes2.1862)
• opportunity to pursue a doctoral degree within the frame-work of the TUM Graduate School
• salary TV-L E13 (65%) for 36 months

Your application

If you are interested in joining our team, please send your application including (1) a letter of motivation with a brief outline of career goals and research experience, (2) a CV/resume, and (3) the contact information of two references. Please send these documents as a single pdf file (StaBio_surname_firstname.pdf) by Nov. 17, 2022 to Dr. Fabian Weikl (stabio.weikl@tum.de). Start date is January 1, 2023 or shortly thereafter.
Do not hesitate to contact Prof. Dr. Thorsten Grams or Dr. Fabian Weikl for any questions you may have.

Ecophysiology of Plants at Land Surface-Atmosphere Interactions (LSAI),
TUM School of Life Sciences,
Prof. Dr. Thorsten Grams,
Carl-von-Carlowitz-Platz 2, 85354 Freising,
Germany,
Tel. +49 8161 714579,
grams@tum.de, https://www.lsai.wzw.tum.de/en/ag-ecophysiology-of-plants/

TUM is an equal opportunity employer. Qualified people of all gender are encouraged to apply. We strive to increase the proportion of women, so applications from women are especially welcome. Applicants with disabilities will be given preference, if they essentially have the same qualifications.

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: Dr. Fabian Weikl: stabio.weikl@tum.de

More Information