Weed control is essential to ensure sustainably crop production and maintain the yield high enough to be economic relevant for farmers. Weed control involves non-chemical technologies (e.g. crop rotation, soil management, sowing period adjustment, etc.) and chemical control of the weed populations by herbicides. Right combinations of these technologies have to be adapted to the local situations in an Integrated Weed Management (IWM) approach. Weed herbicide resistance is a major threat in weed control and its evolution in weed populations is depending on the field history of the past 6-10 years and the different weed management strategies applied. Based on the field history tools to predict resistance and its evolution have been defined and are extremely useful to choose between weed control scenarios to be recommended to farmers. Recently, related to blackgrass in cereal based cropping systems in Germany, we developed two approaches, one on algorithm based on a random forest model and other algorithms based on multigene mathematical models (Thesis Johannes Herrmann, University of Baunschweig / Bayer, CropScience Division) aiming to predict the evolution of the soil seedbank and the frequency of resistance to herbicide in the population analyzed. These models have to be refined, in particular related to local situation in other countries, or/and adapted to other weed species (e.g. rye-grass). In addition the so far developed model(s) are mainly based on target site resistance evolution and the implementation of a module related to metabolic resistance evolution (Richter et al. 2016. Mathematical Biosciences 279: 71-82) should significantly improve the model predictions. Finally a module related to the costs of the different weed control scenarios will help in the decision of the best weed control strategy to be chosen. The aim of the PhD will be:

1. To improve the existing random forest approach and the mathematical model approach related to blackgrass for Germany and other countries.
2. To adapt the models to other weed species, in particular rye-grass
3. To implement and refine two new modules related to metabolic resistance and weed scenario cost evaluation.
4. To explore new modelling approaches, e.g. related to precision farming.

The project will have several aspects. In addition to modeling, weed resistance in populations will have to be evaluated in the field, in the greenhouse and in the laboratory (mutation analyses, herbicide detoxification analyses). We are looking for candidates (Master in Agronomy, Geoecology or related sciences) having proven skills in programing (in particular in R and MATLAB) and model development. Additional skill in agronomy and weed biology, in particular herbicide resistance analyses (bio-test, laboratory analyses) will be an advantage”.

The PhD student will be located at the University of Technology Braunschweig, where theoretical work such as data analysis and model development will be performed. Experimental research and data acquisition will take place in the Bayer AG facilities in Frankfurt (Weed Control Research). The PhD project is a collaboration between Bayer AG and University of Technology Braunschweig under the supervision of Prof. Dr. Otto Richter, Institute of Geoecology.

Salary will be paid according to remuneration level 13 of the wage agreement for public service in the federal states (TV-L13). The position is full-time-job (39.8 hours). Technical University of Braunschweig seeks to increase the number of women in areas in which they are underrepresented. Therefore, we particularly encourage qualified women to apply. Where candidates have the same qualifications, preference will be given to disabled candidates. Applications from international scientists are welcome.

Please send your application including a motivation letter, CV, grades and certificates to Prof. Dr. Otto Richter by February 28, 2018 to following address:

Technische Universität Braunschweig
Institut für Geoökologie, Abteilung: Landschaftsökologie und Umweltsystemanalyse
Prof. Dr. Otto Richter
Langer Kamp 19c
D 38100 Braunschweig.

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