Postdoc Positions on AI for Earth & ClimateDisciplines: Atmospheric Sciences (AS), Biogeosciences (BG), Earth and Space Science Informatics (ESSI)Type: OtherLevel: ExperiencedOpen Required Education: PhDPosted: 19 August 2024We offer 5 postdoctoral positions attached to different European research projects in the intersection of machine learning and Earth and climate sciences. We seek smart and proactive researchers with interest in:Machine Learning (hybrid modeling, GPs, graph neural networks, foundation models, diffusion models, UQ, information theory)Earth Sciences (remote sensing, upscaling, UQ, Gaussian processes, xAI)Climate Sciences (ML-based parametrization, extreme events)The MeDiTwin offers an interesting opportunity to develop your career around capacity building, management, and high-level teaching ML for the Earth sciences.Additional Info:Deadline for applications (extended!): September 6th 2024Interviews for short-listed candidates: September 10-20th 2024Flexible starting dates: From October 2024 to March 2025 (negotiable, depending on the project)All positions are for a duration of 2 years, extendable for an additional 1 year based on mutual satisfaction and agreementFull time or part time, as well as working from abroad is negotiable, depending on the projectYour Profile:Experience in machine learning, deep learning, image processing, statistics, Bayesian inferenceInterest in remote sensing, Earth sciences, climate scienceExperience in scientific interpretation and analysis of dataMotivation for leadership positionsFamiliarity with modeling, model-data-fusion, and machine learningExcellent quantitative skills (e.G., data analysis, modeling)Strong programming skills in Python/Julia/RProven record of scientific publications in international peer-reviewed journalsPhD in maths, physics, or computer scienceCritical and organized sense for data analysisMaturity and commitmentStrong communication, presentation, and writing skills are a big plusCollaborative team playerResponsibilities:Lead research along the project-specific topicsCollaborate with an international team of researchersCoadvise PhD studentsPublish in international peer-reviewed journals and conference venuesCoordinate and report activities of the project, attend project meetingsWhy ISP? The successful candidates will be based in the Universitat de València, Spain. Prof. Camps-Valls is the coordinator of the Image and Signal Processing (ISP) group. The group is devoted to the development of machine learning and signal processing techniques for remote sensing image processing, Earth observation data analysis, and the Geosciences. Several topics are treated in our research group and projects: regression, causality & information theory, Earth observation data analysis, physics-aware machine learning, generative modeling, eXplainable AI and feature ranking, and anomaly detection.#J-18808-Ljbffr
