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Showing posts from August, 2021

Watershed Scientist Position at SFEI

  Dear Colleagues, The San Francisco Estuary Institute (SFEI) is seeking an entry to mid-level watershed scientist to join our Resilient Landscapes Program.  The successful candidate will work on applied science projects relating to watershed restoration, water and sediment management, and climate-change adaptation planning in the Bay Area and statewide. The candidate will help develop tools and quantitative approaches to inform regional and state-wide riverine ecosystem management decisions. The candidate will also help manage projects, coordinate project teams, and work with partners to achieve successful project outcomes. We are looking to fill this position immediately. Applications will be reviewed starting September 13. More information about the position can be found  here . You can get information about SFEI and the Resilient Landscapes Program by visiting our website ( www.sfei.org ). Best, Scott Scott Dusterhoff  Senior Scientist & Lead Geomorphologist San Francisco Estua

3 year postdoctoral research fellow in hydrological modelling

  We invite applications for a   3 year postdoctoral research fellow in hydrological modelling (80%)   in a hydrological and ecological catchment perspective. The position is part of the   Einstein Research Unit “Climate and Water under Change (CliWaC)”, which is a   transdisciplinary   research initiative   of the Berlin University Alliance   to address water-related risks under climate change. CliWaC will bring together social and natural science as well as practical expertise from stakeholders to support the governance of mitigation and adaptation measures in response to climate change.   Further job announcements of CliWaC will be published at: www.cliwac.de/jobs   We seek a dynamic, motivated and ambitious scientist to join an existing interdisciplinary science and modelling team on Landscape Ecohydrology to support the evolution and growth of coupled climate-hydrological-ecohydrological modelling. It is expected that the modelling will utilise outstanding long-term data sets from