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Research scientist / Post-Doc (f/m/d) in remote sensing and ecosystem analysis
Forschungszentrum Jülich GmbH
As a member of the Helmholtz Association, Forschungszentrum Jülich makes an effective contribution to solving major challenges
facing society in the fields of information, energy, and bioeconomy. It focuses on varied tasks in the area of research management and
utilizes large, often unique, scientific infrastructure. Come and work with around 6,100 colleagues across a range of topics and disciplines
at one of Europe's largest research centres.
The Institute of Bio- and Geosciences - Agrosphere (IBG-3) conducts research to improve our understanding of biogeochemical and hydrological processes in terrestrial
systems. A combination of experiments, modelling and innovative observation technologies is used to bridge the gap between model, process and management scale. Its
research contributes to the sustainable and resource-conserving use of soils and water and to the quantification of the effect of climate and land use change on terrestrial
ecosystems. We offer a competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling.
The Project "Digital Agricultural Knowledge and Information System (DAKIS)" contributes to the vision for spatially and functionally diversified agricultural systems
of the future with the aim to accommodate different, and potentially conflicting, environmental and socio-economic objectives. IBG-3 uses remote sensing methods (from
Copernicus, CubeSats, drones) to analyse agricultural cropping systems, variables such as Leaf Area Index and biomass, as well as soil-ecosystem services and their
spatio-temporal patterns. With DAKIS, the effects of agricultural management on the environment will become readily visible and approaches for the reward for ecosystem
services and biodiversity will be enabled.
We are looking to recruit a
Research scientist / Post-Doc in remote sensing and ecosystem analysis
survey of spatio-temporal cropping patterns in agricultural cultivation by remote sensing
workflow development for the calculation of variables for ecosystem simulation (e.g. Leaf Area Index, biomass) by using CubeSats
further development and optimization of techniques for the estimation of soil parameters by vegetation monitoring ("plant as a sensor")
drone measurements (multispectral, thermal, LIDAR) for the validation of satellite retrievals and simulations
soil moisture monitoring (in situ and spaceborne)
estimation of ecosystem services and site analysis for the characterization of cultivation ability of arable crops
contribute to an international research team, publish in international journals and present results at international conferences
university degree (Master, Diploma) in either remote sensing, geosciences, computer science, physics, civil engineering or applied mathematics and a PhD degree in a related field
experience in remote sensing and geoscientific simulation
knowledge in the areas of drone measurements, land surface processes, ecosystem services and numerical methods is a clear advantage
demonstrated programming skills with Python and/or Matlab/Octave
experience in cloud computing by including recent repositories/technologies (Google Earth Engine etc.) is an advantage
ability to work independently as well as collaboratively in an international, interdisciplinary team across institutes; very good communication and organizational skills
good publication record
very good command of the English language, basic German is an asset
vibrant international and interdisciplinary work environment on an attractive research campus, ideally situated between the cities of Cologne, Düsseldorf and Aachen
attendance at national and international conferences and workshops
possibility for further scientific and technical training through international experts
an exceptional research infrastructure
flexible working hours and various opportunities to reconcile work and private life
employment for a fixed term of two years with possible longer-term prospects
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