Group Leader Position in Fluvial Morphology and Biogeochemical Modelling of Stream Ecosystems

Group Leader Position in Fluvial Morphology and Biogeochemical Modelling of Stream Ecosystems

IGB - Leibniz Institute of Freshwater Ecology and Inland Fisheries

Berlin, Germany

The Department of Ecohydrology and Biogeochemistry of the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), located in Berlin-Friedrichshagen on Lake Müggelsee, invites applications for a tenure track group leader position in fluvial morphology and biogeochemical modelling of stream ecosystems. The new group leader is expected to start a research program on linking physical, chemical and ecological process-based models of streams. This position fits IGB ‘s strategic aim to strengthen its capacity for predictive ecology and follows the IGBs commitment and the strategic need to enhance capability in the critical area of coupling fluvial and biogeochemical modelling of stream ecosystems in support of predictive ecology.

Inland flowing waters i.e. streams and rivers are crucial for connecting elements of landscapes and form major components of the global nutrient and carbon cycles. This position aims to understand the functioning of streams, focusing on hydrological, morphological, biogeochemical and ecological components of streams, and their linkages across scales. The position will focus on investigating the impacts of global change on stream ecosystems through advanced, data-driven process-based modelling approaches. The successful candidate will join an existing interdisciplinary science and modelling team to support the strategic development in modelling stream/river ecosystems. Outstanding instrumented research catchments are close to Berlin, access to lab- and field-based data production and to computer clusters is available. Further, the Department builds on a long history of internationally recognized excellence in ecohydrology and biogeochemistry. We are seeking to enhance and complement these existing strengths.

Your role

• Increasing the understanding the functioning of streams through process-based modelling, focusing on hydrological, geomorphological, biogeochemical or ecological components, and their linkages;
• Investigating the impacts of global change on stream ecosystems through advanced stochastic or numerical modelling approaches;
• Development and application of hydrology-based numerical models to predict cross-scale spatio-temporal patterns of fluvial morphology, biogeochemistry or related freshwater biodiversity and interactions with the surrounding landscape;
• Investigation of spatial hydrological and linked ecological processes (linking to metapopulations and meta-ecosystems) in stream networks based on virtual analogues that reproduce topological and scaling features of natural stream networks;
• Simulations of the transport and turnover of environmental or reactive tracers, sediment, nutrients, pollutants and environmental DNA in rivers;
• Scenario simulations of the response of streams to both natural and human-caused disturbances e.g., floods, reservoir construction, channelization, or river restoration;
• Use of these models to assess the effectiveness of sampling strategies and science-based information of land, water and ecosystem management as well as policy making;
• Establish a new research group on linking physical, chemical and ecological process-based models of streams.

Your profile

• PhD in hydrology, or a related field of environmental or geoscience;
• Experience in combining field and modelling insights in process-based understanding of stream ecosystems;
• Excellent numerical/computational skills;
• A strong publication record (commensurate with career stage);
• An established national or international research profile (commensurate with career stage);
• Strong English language skills both in oral and written communication;
• Good track record or potential for raising external research funds (commensurate with career stage).

Additional beneficial requirements would be:

• Good potential for research supervision;
• Expertise in remote sensing and data assimilation Good potential for research supervision;
• Excellent interpersonal skills and proven team-working skills;
• Experience in working in interdisciplinary research projects and collaboration with stakeholders.

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