Sheng Wang

Applications are open for a fully funded PhD position in Remote Sensing for Climate-Smart Agriculture at Aarhus University, Denmark , within the Department of Agroecology and the Pioneer Center Land-CRAFT . This project focuses on developing novel remote sensing algorithms and knowledge-guided machine learning frameworks to monitor crop nitrogen, agroecosystem productivity, and greenhouse gas fluxes for climate-smart agriculture. The work combines hyperspectral, solar-induced fluorescence, multispectral, thermal infrared, passive and active microwave remote sensing with deep learning, radiative transfer modelling, and cloud-computing platforms. Research interests include remote sensing, geoinformatics, agriculture, environmental science, data science, geography, ecology, machine learning, and sustainable crop monitoring. The outputs are intended to inform climate-smart agriculture practices and policies for Danish and EU wheat cropping systems. Eligibility: Applicants should hold an MSc degree in Agriculture, Environmental Sciences, Geoinformatics, Remote Sensing, Data Sciences, Geography, Ecology, or a closely related field. Strong Python/programming skills, experience with large-scale multi-source remote sensing data, and background in crop nitrogen/yield prediction are preferred. English communication skills and interdisciplinary collaboration ability are required. Funding: The position is a 3-year PhD fellowship with salary according to the applicable collective agreement. Deadline: 03 August 2026, 23:59 CEST. The expected start date is 1 November 2026 or later. How to apply: Apply via the Aarhus University application portal. Include the required project description as a PDF and submit before the deadline. Supervisors: Associate Professor Sheng Wang (main supervisor) and Professor Klaus Butterbach-Bahl (co-supervisor).