Experiencia: Según bases
The position is hosted in the Climate Prediction Group (CPG) within BSCs Earth Science Department. The Climate Prediction Group aims at developing climate prediction capability for time scales ranging from a few weeks to a multiple decades into the future, and from regional to global scales. More recently, the CPG has been developing an expertise on near-term prediction and projection of the global carbon cycle with the EC-Earth-CC Earth System Model.
The offered position is funded by the European H2020 projects LANDMARC and 4C. LANDMARC explores the potentials for land-based climate change mitigation, whereas the 4C project aims to establish near-term prediction systems of climate and atmospheric CO2 growth rate to assist the implementation of the Paris agreement.
The successful applicant will contribute within the LANDMARC project to the development of a modelling system which integrates a global land-use model into an Earth System Model in order to study the effects of LMT (Land-based mitigation technology) scenarios on the global carbon cycle and atmospheric processes. The applicant will also participate in the 4C project to study the contribution of vegetation and land-use change to atmospheric CO2 variability and predictability. The candidate will as well have the opportunity to contribute to the scientific planning and development of the next generation of the EC-Earth ESM, version 4.
Contribute to the development of a model system that combines a global land-use model with an earth system model, focusing on the vegetation/land use aspects
Analyze the experiments performed using the model system and LMT scenarios developed in the LANDMARC project, in regard of effects on land-use change, the carbon cycle and atmospheric processes
Analyze the contributions of vegetation and land-use change to near-time prediction of the global carbon cycle
Participate in networking, dissemination, publication and grant preparation activities
The candidate will work closely with scientists within the Climate Prediction Group and other groups of the Earth Sciences Department
PhD in ecology, atmospheric or climate science, or a related discipline
Essential Knowledge and Professional Experience
Experience in working with Dynamic Vegetation models and/or Land-use change models. Experience with LPJ-GUESS is highly valued.
Proven ability to prepare and submit manuscripts to peer-reviewed scientific journals
Well-established scientific network in vegetation, land-use and climate modelling
A demonstrated ability to analyse climate and vegetation data
Programming skills: scripting (e.g. bash, python), programming (Fortran, c++) data analysis and visualization software (e.g. CDO, NCO, R, Python, QGis)
Additional Knowledge and Professional Experience
Interest and capacity in participating in the writing and, when possible, leading the preparation of research and computing proposals
Knowledge of version control systems (git, svn, cvs )
Interest in tutoring and/or advising master and PhD students
Previous postdoctoral experience will be valued
Fluency in spoken and written English, while fluency in other European languages will be also valued
Highly collaborative spirit and ability to work as part of a large, strongly-coordinated team and to continuously share both knowledge and tools
Origen: Información recogida a través de cido.diba.cat
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