Post-doctoral position in tree and forest modelling
We are looking for excellent candidates for post-doc position in tree and forest modelling in the Inverse Problem Research Group of Tampere University of Technology (http://math.tut.fi/inversegroup/). The Group has done pioneering work on the quantitative structure modelling of trees from point cloud data and their applications on, e.g., biomass estimation, species recognition, change detection, and visualization. The Group has a large international collaborating network of experts on remote sensing, forestry, forest research, and ecology. The main focus is on basic research leading to scientific breakthroughs on tree and forest modelling from laser scanner and other data, but more applied research is also welcomed.
We offer many possible topics of research, including: methods for reconstructing quantitative structure models (QSMs) of forests, automatic tree extraction from point cloud data, eco-physiological modelling of trees using QSMs, tree growth modelling and 4D functional-structural models, machine learning methods for LiDAR data processing and classification, and other forestry and ecology applications. The particular research topics will be discussed and planned to fit the research background and the main interests of the applicant.
The applicant for the position is required to hold a PhD degree in mathematics, computer science, theoretical ecology, mathematical and theoretical biology, biological physics, chemistry, or a related area. The applicant’s research background should be relevant to the position. We appreciate good programming skills (e.g., c, c++, python, matlab).
-Start: April 2018 or as soon as possible.
-Duration: 2 years with possible extension
-A short motivation letter describing your background and research experience in relevant fields as well as your research interests in general
-List of publications (the most relevant publications highlighted)
-Two references with contact information