Doctoral student in satellite observations: deriving climate data by physically-based machine learning

Join the Division of Geoscience and Remote Sensing at Chalmers University of Technology as a doctoral student and contribute to the development of novel climate data by leveraging Europe's latest satellite sensors. The division is part of the Department of Space, Earth and Environment, focusing on advanced methods and instruments to observe and understand the Earth system. The research project centers on the upcoming launch of satellites equipped with the MicroWave Imager (MWI) and Ice Cloud Imager (ICI), with the team playing a leading role in preparing for ICI and deriving essential climate data on ice clouds. This doctoral project aims to extend data extraction by jointly using measurements from MWI and ICI, enabling the derivation of geophysical data on all forms of atmospheric water (gas, liquid, and ice). The approach is based on machine learning, specifically quantile regression neural networks, and requires simulating satellite observations due to the absence of ground-truth data. The foundation of the project involves detailed physical simulations encompassing atmospheric science, radiative transfer, and sensor characteristics, pushing the boundaries of large-scale physical simulations. The outcomes will contribute to official data products distributed by EUMETSAT and research products disseminated by the team. Additional tasks may include improving the Atmospheric Radiative Transfer Simulator ( https://www.radiativetransfer.org/ ), verifying climate models with derived geophysical data, and applying developments to the Arctic Weather Satellite and Sterna missions. The research team is led by Prof. Patrick Eriksson ( https://orcid.org/0000-0002-8475-0479 ), and more information about datasets is available at https://clouds-and-precip.group . As a doctoral student, you will take advanced courses, develop scientific concepts, and communicate research results. The position includes teaching or other duties up to 20% of working hours. The contract is fully funded, with a starting salary of 34,550 SEK per month, and offers employee benefits. The appointment is for four years, extendable to five years with teaching duties. Physical presence is required throughout the study period, and a valid residence permit must be presented by the start date. Applicants must have a relevant Master's degree or, for non-Swedish education, a 4-year Bachelor's degree. Strong skills in physics and computing, proficiency in English, and the ability to start by August 1, 2026, are mandatory. Experience in atmospheric science, radiative transfer, remote sensing, Python, and deep learning frameworks (e.g., PyTorch) is advantageous. Chalmers offers a dynamic and inclusive environment, with support for gender equality and diversity, and provides Swedish courses for non-native speakers. To apply, submit your application in English as PDF files (CV, personal letter, introduction, motivation, thesis, transcripts) via the online form ( application link ). Ensure completeness, as incomplete or emailed applications will not be considered. The deadline is March 8, 2026. For questions, contact Anqi Li ([email protected]) or Prof. Patrick Eriksson ([email protected]).