2-year Postdoc (100%) or 3-year PhD (75%) (m/f/d)

at  PotsdamInstitut fr Klimafolgenforschung PIK e V

The climate needs bright minds. The Potsdam Institute for Climate Impact Research (PIK) addresses crucial scientific questions in the fields of global change, climate impacts and sustainable development. It is one of the world’s leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research.
For the working group “Machine Learning” PIK is offering a
2-year Postdoc (100%) or 3-year PhD (75%) (m/f/d)
(Position number: 63-2024 Postdoc Machine Learning)
position in the field of Machine Learning for Emulation of Earth system models, starting on 01.07.2025.
Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13 This is a full-time position with a weekly working time of 40 hours per week. The position can be filled on a part-time basis.
The position is funded via the HorizonEurope project “Past to Future: Towards fully plaeo-informed future climate projections”, which will start on January 1st 2025. This large EU project with 24 partners aims to advance Earth system models with regard to improved reproduction of climate variability as evidenced in paleoclimate proxy archives, including model re-calibrations and development of new, efficient model components also using machine learning approaches.

REQUIREMENTS:

• MSc (when applying for the PhD position) or PhD (when applying for the Postdoc position) in applied mathematics, machine learning, physics, meteorology or related field
• Experience with machine learning methods is required
• Experience in developing and running Earth system models is of advantage
• Experience with paleoclimate proxy data and / or Earth system model simulations is of advantage

• Development of ML-based emulators of process-based Earth system model components
• Development of methods for efficient re-callibration of Earth system models for improved representation of paleoclimate variability
• Collaboration with other project partners regarding re-calibration of Earth system models
• Scientific publications reporting on project outcomes