PhD Position in Earth System Modelling and Machine Learning for Amazon Early Warning Systems
At the Technical University of Munich (TUM), within the Earth System Modelling Group and the Munich Climate Center, we invite applications for one PhD position (m/f/d) to work on the development of an Amazonian Early Warning System (AmEWS) integrating Earth Observation data, process-based ecosystem models, and advanced machine learning approaches.
Key Responsibilities
- Develop and apply machine learning methods (e.g. CNNs, hybrid ML–process-based models) for predicting ecosystem disturbances and risks
- Integrate process-based vegetation and Earth system models with data-driven components
- Analyze single and compound hazards affecting Amazon forest resilience
- Contribute to the design and implementation of an early warning platform for scientific and policy-relevant applications
- Publish results in peer-reviewed journals and present them at international conferences
- Collaborate closely with researchers at TUM and partner institutions in Brazil
Requirements
- A Masters degree in physics, computer science, Earth system sciences, ecology, mathematics, or a related field
- Strong programming skills, preferably in Python (experience with scientific computing, ML frameworks, high performance computing and geospatial data are highly desirable)
- Interest or experience in Earth system modelling, remote sensing, and/or machine learning
- Ability to work independently and collaboratively in an interdisciplinary environment
- High proficiency in written and spoken English
- Willingness to engage in international collaboration and research stays
Benefits
- The chance to be part of an interdisciplinary collaboration of leading international research institutions
- Participation at international workshops and conferences
- A stimulating working environment in an internationally leading research institution
- A collective pay scheme and associated benefits