PhD position-Feedbacks between vegetation and climate

The Potsdam Institute for Climate Impact Research (PIK), the Humboldt University Berlin and the Instituto Nacional de Pesquisas Espaciais (INPE), Brazil, offer training and excellent research opportunities for outstanding PhD students within the International Research Training Group on “Dynamical Phenomena in Complex Networks”. Within the IRTG it is intended to study principles of self-organization in evolving complex networks. The theoretical studies will be intimately connected with the investigation of experimental and natural dynamical networks of increasing complexity starting from lasers, via hybrid networks of neurons to the Earth system. In this context, the main topic will be to understand the functioning of the Earth´s subsystems under changing conditions, especially global warming and deforestation in Amazonia. The training program includes dual supervision of each student, annual schools and workshops in Germany and Brazil. Doctoral researchers are required to spe
 nd a period of up to 6 month in the overseas partner group.
The project addresses the question of how changes in land cover and use, especially deforestation by means of fire, modifies the vegetation cover and atmospheric composition. To investigate and better understand these feedbacks between vegetation and the atmosphere we need to quantify the potential for an “Amazon tipping point”.

Methoden:
The PhD student will work with a dynamic vegetation model (LPJmL) and contribute to the coupling of a regional climate-vegetation model (CCLM). The modelling results will be used in complex network analysis to identify tipping points and teleconnections in climate.

Anfangsdatum: 17. November 2011

geschätzte Dauer: Three (3) years

Bezahlung: 1365 EUR/month, plus a research allowance of 103 EUR/month

Veröffentlichungen:
Please send your application (a brief statement of research interests, a CV and full contact information for 1-2 referees)

Homepage: http://www.physik.hu-berlin.de/irtg1740/information

Qualifications:
- University degree at the Master/Diploma level in environmental sciences, geoecology, climatology, physics, system science. In a few exceptional cases outstanding applicant with a Bachelor’s degree may be considered.
- Experience with data analysis, programming and computational modeling
- Motivation to work in a multi-disciplinary team
- Excellent knowledge of English language (written and spoken) is indispensable