PhD Position in Earth System Modelling and Machine Learning for Amazon Early Warning Systems

09.03.2026, Academic staff

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.

The position is embedded in a close international collaboration between TUM, the newly founded Instituto Relva and other leading Brazilian institutions. The successful applicant will work under the supervision of Prof. Dr. Marina Hirota and Prof. Dr. Niklas Boers. The position is funded for 3 years (PhD, 30h per week). Remuneration is in accordance with the German public tariff scheme (TV-L), salary group E 13.

About the Project

This project aims to develop the Amazonian Early Warning System (AmEWS) - a near real time, data- and model-driven platform that focuses on multi-hazard risk prediction for the Amazon rainforest, including droughts, fires, and deforestation, as well as ecosystem resilience and tipping points.

Key Responsibilities

The successful PhD candidate will:

• 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 Master’s 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

We Offer

• 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

Equal Opportunity Statement

TUM is committed to promoting equal opportunities. We explicitly encourage applications from women and underrepresented groups. In cases of equal qualification, women will be given preference within the framework of applicable law. Applications from candidates with disabilities or a migration background are explicitly welcome.

Application Procedure

We explicitly encourage women to apply. In cases of equal qualification and within the given legal scope, women will be given preference. Applications by candidates with migration background are also encouraged. Disabled candidates with equal qualifications will be regarded favorably. We also encourage applications by parents returning from parental leave. Please send your full application (including cover letter, CV with list of publications, contact details of two referees, Master certificates) as a single PDF document by email to esm-jobs.asg@ed.tum.de. Deadline for applications is March 29, 2026. The size of the file should not exceed 15 MB. For further information or to discuss the position please contact Prof. Dr. Marina Hirota (marinahirota@gmail.com).

Data Privacy Notice:

When applying for a position at the Technical University of Munich (TUM), you submit personal data. Please note our data privacy information pursuant to Article 13 of the General Data Protection Regulation (GDPR) regarding the collection and processing of personal data in connection with your application. By submitting your application, you confirm that you have read and understood TUM's data privacy notice.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: esm-jobs.asg@ed.tum.de