Atkinson Postdoctoral Science Fellow, Methane

EDF fellowships provide high-quality experiences, including relevant projects and opportunities for networking, that form the foundation serious candidates need to pursue an environmental career. Location Any EDF U.S. office location (Austin, TX; Boulder, CO; Boston, MA; New York, NY; Raleigh, NC; San Francisco, CA; Washington D.C.) or U.S. Remote. Fellow supervisor is in British Columbia, Canada and many team members are in Massachusetts & Texas. Eligibility to work in the U.S. is required for the duration of the fellowship. Duration 2 years (with an anticipated start date of June 8, 2026) Application Materials Interested applicants should attach their cover letter and CV that includes peer-reviewed publications or any manuscripts in preparation as part of the EDF application. Program/Department Overview Science & Innovation (S&I) is the nexus of science at EDF, ensuring that the science that is the backbone for all EDF policy positions is based on the best available information. To be most effective in this role, S&I provides programmatic support for all scientists at EDF and fosters relationships with scientists outside the organization. Within S&I, the Global Methane Science Team has been at the forefront of global methane research and mitigation action for over a decade. The team has helped elevate methane to the center of international climate negotiations and has pioneered the development and application of innovative technologies and scientific approaches to accelerate emissions reductions. Building on this foundation, the team is working toward ambitious 2030 goals: reducing methane emissions by 75% from the oil and gas sector and 40% from the livestock sector, relative to 2020 levels. Overall Function This position, as a joint EDF-Cornell Postdoctoral Research Fellowship, will lead efforts to map methane-emitting infrastructure and activities across key regions in East Asia. The Postdoctoral Fellow will develop a comprehensive, high-resolution geospatial dataset of methane emission sources, spanning the oil and gas supply chain, coal mines, wastewater treatment facilities, landfills, dairy farms, rice paddies, and wetlands. The resulting dataset will support robust interpretation of satellite observations (e.g., TROPOMI, GOSAT-GW, and MethaneSAT), advance scientific understanding of regional methane emissions, and provide actionable evidence to inform effective methane mitigation policies and regulations. The Postdoctoral Fellow will report to a Senior Scientist within the Global Methane Science Team at EDF, as well as a Professor in the Department of Computer Science at Cornell University. Key Responsibilities Tasks will include but are not limited to: Compile infrastructure data on methane emission sources from publicly available resources, including government reports, websites, peer-reviewed literature, and Earth observation imagery. Analyze, integrate, and visualize geospatial data using appropriate tools, and develop structured geospatial datasets. Conduct systematic reviews to identify and synthesize information on methane-emitting activities across multiple sectors. Collect and manage web-based data using responsible data collection practices, including automated extraction where permitted and in compliance with applicable terms of use. Apply data processing and analytical methods, including AI-based approaches where appropriate, to support the identification and mapping of methane-emitting infrastructure. Write at least one paper for publication in a peer-reviewed journal, and contribute to grant proposals, and other written materials. Prepare clear, well-documented reports, datasets, and technical summaries. Communicate progress, findings, and challenges effectively with team members and collaborators across EDF and Cornell. Participate in advancing EDF’s organizational effectiveness and culture goals, so people from all backgrounds and experiences feel connected, included and empowered to address environmental and organizational challenges in ways that align with EDF values. Qualifications A recent PhD in Atmospheric Science, Computer Science, Geospatial Science, Environmental Science, Earth System Science, Engineering, or a related field. Strong experience in Remote Sensing including analyzing and interpreting satellite or aerial imagery, including Earth observation datasets (e.g., Sentinel, Landsat, or similar platforms). Experience with geospatial data processing and GIS tools (e.g., ArcGIS, QGIS, or equivalent). Demonstrated experience applying machine learning and/or computer vision techniques to image-based data, including object detection, image classification, or semantic segmentation. Familiarity with environmental systems, infrastructure mapping, or greenhouse gas emissions analysis is highly desirable. Proficiency in programming for data analysis and geospatial workflows (e.g., Python, R, or similar). Experience integrating heterogeneous data sources, including remote sensing data, publicly available datasets, and web-based information sources. Strong analytical skills and ability to work independently in a research-driven, interdisciplinary environment. Excellent written and verbal communication skills, with experience preparing technical documentation or research outputs. Proven ability to collaborate effectively across disciplines, including environmental science, data science, and policy-relevant research domains. Proficiency in Mandarin Chinese is considered an asset for engaging with regionally relevant information sources in East Asia, but not required. Demonstrate self-awareness, cultural competency and inclusivity, and ability to work with colleagues and stakeholders across all cultures and backgrounds. Demonstrate initiative and problem solving skills. Compensation We offer a strong total rewards package encompassing competitive salary, robust benefits, and professional development opportunities consistent with a modern global organization. The annual salary for this role is$72,000. Learn more about fellowships at EDF -

72,000 - 72,000 USD

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