Ecoinformatics, Biometrics and Forest Growth

Ph.D. thesis topics offers





Currently offered PhD topics at the Department of Ecoinformatics, Biometrics and Forest Growth (principal supervisor: Prof. W. Kurth)




Integration of the xylem sap flow model HYDRA and of a soil water model into a rule-based framework and test at oak and spruce trees


Design and implementation of an intelligent data interface between an electromagnetic 3-d digitizer and a graph-based modelling software


Implementation, application and analysis of selected algorithms for grid-based discretization and fractal analysis of virtual 3D structures


Extension of the 3-d modelling software GroIMP to a multi-user virtual reality environment for e-training in forestry


Implementation of the structural plant simulator AmapSim as a system of graph transformation rules in the language XL. Model comparison and application to Sugar Maple (Acer saccharum) and Teak (Tectona grandis)


Theory and design of an interactive visual programming system for functional-structural plant models and implementation as an extension of the tools GroIMP and XL


A 3-dimensional model of apple tree growth and development, including light interception and biomechanics






Application for a PhD project topic and for an invitation letter (for external applicants)

The following documents are required as parts of a single pdf file (except the last item):


  • Cover sheet: first page of your application (already indicating your name, e-mail address, preferred topic / field of research ... )
  • Curriculum Vitae with a photo
  • Certificates and official transcript / Record of study: certificates such as B. Sc. and M. Sc.; detailed documentation of your academic work, i.e. list of courses at all colleges / universities attended, grades if applicable; list of publications if there are any.
  • Proof of proficiency in English or German language
  • Two reference letters: it is recommended to submit signed letters of two academic teachers who are able to evaluate your personality, academic experience, and intellectual merit, e.g. from your M.Sc. thesis supervisor.