Postdoc Positions on AI for Earth & Climate
Disciplines: Atmospheric Sciences (AS), Biogeosciences (BG), Earth and Space Science Informatics (ESSI)
Type: Other
Level: Experienced
Open Required Education: PhD
Posted: 19 August 2024
We 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 2024
Interviews for short-listed candidates: September 10-20th 2024
Flexible 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 agreement
Full time or part time, as well as working from abroad is negotiable, depending on the project
Your Profile:
Experience in machine learning, deep learning, image processing, statistics, Bayesian inference
Interest in remote sensing, Earth sciences, climate science
Experience in scientific interpretation and analysis of data
Motivation for leadership positions
Familiarity with modeling, model-data-fusion, and machine learning
Excellent quantitative skills (e.g., data analysis, modeling)
Strong programming skills in Python/Julia/R
Proven record of scientific publications in international peer-reviewed journals
PhD in maths, physics, or computer science
Critical and organized sense for data analysis
Maturity and commitment
Strong communication, presentation, and writing skills are a big plus
Collaborative team player
Responsibilities:
Lead research along the project-specific topics
Collaborate with an international team of researchers
Coadvise PhD students
Publish in international peer-reviewed journals and conference venues
Coordinate and report activities of the project, attend project meetings
Why 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.
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