The PhD
position is embedded in a DFG (German Research Foundation) funded
project which aims at the quantification of uncertainties of simulated
biosphere-atmosphere –hydrosphere fluxes of C and N compounds and
ecosystem C and N stock changes at regional scale due to input,
parametric and structural model uncertainties.
Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.
In the frame of the project “Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change“ the PhD candidate, in cooperation with our partners at the University of Giessen, will develop a process-oriented landscape model that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes. For this the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behavior, will be coupled to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.
Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty of fluxes of interest
(e.g. greenhouse gas emissions) is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.
We seek a Ph.D. student to specifically address the research topics by developing suitable assessment and quantification approaches using a coupled hydro-biogeochemical model and deploying it on high performance computing (HPC) infrastructures across Germany. The successful candidate will address the following topics:
• Uncertainty assessment of coupled model systems at site level by setting up and deploying a coupled hydrological - biogeochemical model
• Regional model application and uncertainties assessment by identifying the best spatial data resolution, model calibration and uncertainty assessment
• Feedback of regional C, N and water fluxes on land use, climate change and impact on water and nutrient fluxes on the landscape scale
• Probabilistic and deterministic ensemble predictions
We offer a position in a well established and worldwide acknowledged research team with excellent research infrastructure and support. We are well connected to national and international research programmes.
Salary will be 65% of a TV-L E13 position.
The Ph.D. position will be for a maximum period of three years. The student will have the opportunity to participate in a variety of courses, for instance offered by the Research School MICMoR (http://www.micmor.kit.edu/).
Requirements
• Strong background in computing (Unix, Linux, HPC) and programming
• Strong background in at least one topic of biogeochemistry, hydrology, meteorology, physics, mathematics, engineering or computer science
• Background of stochastic simulation is preferable
• Aptitude to learn and work with complex models and HPC environments
• Sense of responsibility, ability to meet deadlines, enjoyment of working within a multi-disciplinary research team
• Master of Science or Diploma which allows to conduct a doctoral study at the University of Freiburg, Faculty of Forest and Environmental Sciences
The Karlsruhe Institute of Technology (KIT) is the fusion of the former University of Karlsruhe and the Forschungszentrum Karlsruhe. This makes KIT a unique institution in Germany, combining the missions of a university and that of a national research centre in the Helmholtz-Association. With a staff of 8000 and an annual budget of EUR 650 Mio., KIT ranks among the largest institutions of research and higher learning worldwide.
Applications including curriculum vitae, certificates, short outline of own interests and skills regarding the position's profile, and contact information of two professional referees shall be addressed to
Prof. Dr. Klaus Butterbach-Bahl
Head of Division Biogeochemical Processes,
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU), D 82467 Garmisch-Partenkirchen, Germany; E-mail: klaus.butterbach-bahl@kit.edu
Complete applications received by 30 January 2013 will receive full consideration but the position will remain open until a suitable candidate has been identified.
KIT strives to achieve gender balance at all levels of employment. We therefore particularly encourage female candidates to apply for this position. With appropriate qualifications, applications from persons with handicaps will be treated with preference.
Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.
In the frame of the project “Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change“ the PhD candidate, in cooperation with our partners at the University of Giessen, will develop a process-oriented landscape model that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes. For this the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behavior, will be coupled to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.
Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty of fluxes of interest
(e.g. greenhouse gas emissions) is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.
We seek a Ph.D. student to specifically address the research topics by developing suitable assessment and quantification approaches using a coupled hydro-biogeochemical model and deploying it on high performance computing (HPC) infrastructures across Germany. The successful candidate will address the following topics:
• Uncertainty assessment of coupled model systems at site level by setting up and deploying a coupled hydrological - biogeochemical model
• Regional model application and uncertainties assessment by identifying the best spatial data resolution, model calibration and uncertainty assessment
• Feedback of regional C, N and water fluxes on land use, climate change and impact on water and nutrient fluxes on the landscape scale
• Probabilistic and deterministic ensemble predictions
We offer a position in a well established and worldwide acknowledged research team with excellent research infrastructure and support. We are well connected to national and international research programmes.
Salary will be 65% of a TV-L E13 position.
The Ph.D. position will be for a maximum period of three years. The student will have the opportunity to participate in a variety of courses, for instance offered by the Research School MICMoR (http://www.micmor.kit.edu/).
Requirements
• Strong background in computing (Unix, Linux, HPC) and programming
• Strong background in at least one topic of biogeochemistry, hydrology, meteorology, physics, mathematics, engineering or computer science
• Background of stochastic simulation is preferable
• Aptitude to learn and work with complex models and HPC environments
• Sense of responsibility, ability to meet deadlines, enjoyment of working within a multi-disciplinary research team
• Master of Science or Diploma which allows to conduct a doctoral study at the University of Freiburg, Faculty of Forest and Environmental Sciences
The Karlsruhe Institute of Technology (KIT) is the fusion of the former University of Karlsruhe and the Forschungszentrum Karlsruhe. This makes KIT a unique institution in Germany, combining the missions of a university and that of a national research centre in the Helmholtz-Association. With a staff of 8000 and an annual budget of EUR 650 Mio., KIT ranks among the largest institutions of research and higher learning worldwide.
Applications including curriculum vitae, certificates, short outline of own interests and skills regarding the position's profile, and contact information of two professional referees shall be addressed to
Prof. Dr. Klaus Butterbach-Bahl
Head of Division Biogeochemical Processes,
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU), D 82467 Garmisch-Partenkirchen, Germany; E-mail: klaus.butterbach-bahl@kit.edu
Complete applications received by 30 January 2013 will receive full consideration but the position will remain open until a suitable candidate has been identified.
KIT strives to achieve gender balance at all levels of employment. We therefore particularly encourage female candidates to apply for this position. With appropriate qualifications, applications from persons with handicaps will be treated with preference.
Application Deadline : 30 January 2013
