Postdoctoral Fellow

Fully Funded PhD Position – Coastal Geomorphology | University of Maryland Institution: University of Maryland, College Park – Department of Geographical Sciences Location: College Park, Maryland, USA Research Area: Coastal Geomorphology | Coastal Processes | Sediment Transport | Coastal Hazards | Wetland Dynamics | Geospatial Analysis | Environmental Modeling The Department of Geographical Sciences at the University of Maryland, College Park , is recruiting 1–2 fully funded PhD students to join the research group of Dr. Danghan Xie , beginning in Fall 2027 . The research focuses on understanding coastal morphodynamics, sediment transport, coastal hazards, wetland evolution, and coastal processes using field observations, geospatial data, and process-based and data-driven modeling approaches. Funding is provided through a teaching and/or research assistantship , including a stipend and full tuition remission . What You’ll Work On Investigate coastal morphodynamics and sediment transport to understand how coastal landscapes evolve over time. Study coastal flooding and coastal hazards and develop approaches for assessing coastal vulnerability and risk. Coastal Wetland Dynamics Research coastal wetland evolution and dynamics , examining the physical processes that influence coastal ecosystems. Geospatial & Remote Sensing Analysis Integrate LiDAR, satellite imagery, drone data, and field observations with coastal process models to understand coastal environments. Coastal Process Modeling Develop and apply process-based, data-driven, and physics-guided models for coastal system analysis and prediction. Quantitative Research Use quantitative and computational approaches to analyze coastal processes, environmental data, and geomorphic change. Ideal Candidates Applicants should hold a B.S. or M.S. degree in one of the following or a related field: Geography Oceanography Related disciplines Preferred skills include: Hydrodynamics Sediment transport Geomorphology Numerical modeling GIS Remote sensing Geospatial data analysis Programming with Python, MATLAB, R, or similar tools Students with strengths in either process-based modeling or geospatial/data analysis who are interested in developing complementary skills are particularly encouraged to apply. What You’ll Gain Opportunity to conduct research in coastal geomorphology and environmental sciences . Fully funded PhD support through a teaching and/or research assistantship . Stipend and full tuition remission . Opportunity to work with coastal process models and geospatial datasets. Experience integrating field observations, LiDAR, satellite, and drone data . Training in numerical modeling, GIS, remote sensing, and quantitative analysis. Opportunity to work in a collaborative research environment near the Washington, D.C. metropolitan area . Exposure to interdisciplinary research involving coastal processes, hazards, wetlands, and environmental change. Program: PhD in Geographical Sciences Funding: Fully Funded Funding Type: Teaching and/or Research Assistantship Tuition: Full Tuition Remission Stipend: Provided through the assistantship Positions: 1–2 PhD Students Start Term: Fall 2027 Location: College Park, Maryland, USA About the PI Dr. Danghan Xie is an Assistant Professor in the Department of Geographical Sciences at the University of Maryland, College Park . His research integrates coastal process modeling, field observations, and geospatial data to understand coastal morphodynamics, sediment transport, wetland evolution, and coastal hazards. Category PhD Position | Fully Funded PhD | Coastal Geomorphology | Geography | Geosciences | Environmental Science | Oceanography | Coastal Research | Sediment Transport | GIS | Remote Sensing | Geospatial Analysis | Research Jobs | USA PhD | University Jobs Tags #PhDPosition #FullyFundedPhD #UniversityOfMaryland #CoastalGeomorphology #Geography #Geosciences #CoastalResearch #SedimentTransport #GIS #RemoteSensing Your email address will not be published. Required fields are marked * Comment * Name * Email * Website #J-18808-Ljbffr