Postdoc \"Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...

Area of research:

Scientific / postdoctoral posts

Job description:

Postdoc \“Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Foundation Model\“ (m/f/d)

Background

The large collaborative project ‘3D-ABC’, funded for 3 years by the Helmholtz Foundation Model Initiative, focuses on developing a Foundation Model that combines large remote sensing and field datasets, AI, generative AI, and Exascale HPC to analyze the global carbon cycle at high resolution, emphasizing terrestrial carbon stocks.

Led by AWI, the project involves 6 HGF centres and utilizes diverse datasets including TanDEM-X radar data, LiDAR, and other remote sensing data. The project aims to facilitate various tasks from land cover change to complex carbon impact assessments, requiring extensive data processing on HPC systems like JUWELS and JUPITER.

Focus of the position

This postdoc role involves processing TanDEM-X interferometric data for the 3D-ABC Foundation Model, analyzing the results, and supporting downstream tasks related to forest height and biomass. You will also manage data transfer between teams. Essential skills include handling large-scale SAR data, programming, and basic AI knowledge.

Your Tasks

1. Interpret data requirements for model training and downstream tasks, focusing on forest and permafrost areas.
2. Retrieve, process, and store TanDEM-X data as per project specifications.
3. Transfer processed data efficiently within the consortium.
4. Develop data management and processing interfaces.
5. Analyze results and support validation of downstream tasks.
6. Utilize hardware and software resources at DLR Oberpfaffenhofen during full-time stays.

Your Profile

• Doctoral degree in remote sensing, signal processing, computer science, or related fields.
• Experience with large-scale remote sensing SAR data processing and analysis.
• Programming skills and automation experience.
• Interest in interferometric SAR data for AI and FM training.
• Basic AI knowledge and dataset requirements understanding.
• Strong publication record and presentation skills.
• Ability to work independently and in teams internationally.
• Proficiency in English (CEFR B1 or higher).

Preferred Qualifications and Skills

• Knowledge of SAR interferometry and inversion.
• Experience with Deep Learning and Foundation Models.
• Prior work with forest-region SAR datasets.
• German language skills.

Further Information

AWI offers an excellent research environment, international collaboration, flexible working hours, health promotion, and support for work-life balance. The institute values diversity and gender parity, welcoming applications from all backgrounds. Applicants with disabilities will be prioritized if qualifications are equal. Support services are available to help new employees settle in.

This center is part of the Helmholtz Association, Germany\’s largest scientific organization.

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