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A research institute in Germany is seeking a scientist to conduct analyses and gather data on inland fisheries. The position focuses on species in northern Germany, requiring a doctoral degree and experience in fisheries population dynamics. Responsibilities include organizing data collection, developing population models, and publishing findings in scientific journals. Candidates must have strong statistical program expertise and the ability to communicate in English effectively. A valid work permit in Germany is necessary for the position.
Inland fisheries are globally recognized for their importance in providing locally sourced protein, offering recreational uses and supporting livelihoods. Sustainable fishing is key to ensuring that these benefits are available in the future, and reliable information on population dynamics and stock status can help sustain vital stocks in the long run. A key challenge of inland fisheries is collecting sufficient data from many relatively small waterbodies driven by external factors, and then effectively using collected data to compare and evaluate fishery management options. Small-scale inland fisheries are thus often characterized as data-poor, while also being subject to rapid environmental changes. Assessing population status and identifying sustainable management strategies are thus especially challenging.
We are seeking a scientist to collect data and conduct analyses to describe population dynamics, the role of environmental covariates, and assess stock status of inland fisheries in northern Germany. The project focuses specifically on assessing vendace stocks in lakes, pike perch in the lower Havel River, and collecting preparatory data and parameters for other species. The results of this challenging endeavor will be used to help develop recommendations for sustainable fishing practices and monitoring strategies. Findings will be published in peer-reviewed journal articles as well as magazines and newsletters for local fishers, anglers, and stakeholders.
Tasks
Minimum Qualifications
Preferred Qualifications