Internal Research Fellow (Post-Doctoral) in AI Onboard for Synthetic Aperture Radar (SAR) Missions

Our team and mission

Reporting to the Head of the Explore Office in the ESA Φ-lab, you will work in close cooperation with other staff in the Directorate of Earth Observation Programmes.

You will be part of the ESA Φ-lab. Our mission is to accelerate the future of Earth Observation (EO) by embracing disruptive innovation and acting as a catalyst for disruptive/transformative innovation in the sector. Our vision is to become an “EO innovation hub” connecting a growing ecosystem of disruptive and transformative innovation like AI, ML, Quantum Computing, Edge Computing, etc.. with EO. Many of the challenges posed by new digital technologies still need to be tackled at scientific, application and capability level to deliver maximum value from satellite-derived EO assets for our climate, society and economy. The Φ-lab will bring together early career and senior researchers from a variety of disciplines across EO and disruptive/transformative innovation to help develop innovative EO solutions.

We offer:

•   a stimulating multinational and interdisciplinary open work environment;
•   access to high-performance computing infrastructure and dedicated EO and technology expertise;
•   a unique opportunity to work on innovative solutions to address global problems;
•   freedom and focus to conduct creative research while making an impact related to ESA strategy;
•   a wide network of relationships and collaborations with top academics, industry and research centres;
•   the possibility to contribute to the Φ-lab’s strategy and activities.

You are encouraged to visit the ESA website: https://www.esa.int/

Field(s) of activity/research for the traineeship

While onboard intelligence for Earth Observation (EO) has seen notable advancements, attention towards Synthetic Aperture Radar (SAR) technology has been disproportionately limited compared to optical sensors. These sensors have stood out due to their high-resolution imagery and familiarity, despite being hindered by cloud cover and darkness. In contrast, SAR offers unparalleled capabilities, such as all-weather and day-and-night imaging, crucial for continuous monitoring and rapid response applications such as disaster management and maritime surveillance. Despite SAR's immense potential, its implementation of onboard intelligence remains relatively underexplored. The complexities associated with SAR data, including unfocused raw data and intricate interactions with the Earth's surface properties, present both challenges and opportunities for integrating intelligent decision-making processes directly into SAR-equipped spacecraft. This fellowship will seek to address the gap in onboard intelligence for SAR-based EO applications, especially in the context of Copernicus Sentinel-1 Next Generation, for launch in the 2035 horizon. The goal is to propel the development of advanced AI-based algorithms that harness onboard the unique capabilities of SAR sensors while ensuring real-time analysis, early detection, decision-making, and quality assessment, thereby minimising reliance on standard ground receiving stations and ground-based processing.

In your application, please provide a research proposal (of no more than five pages) describing a relevant theme of interest and the expected results.

In particular, you will:

• undertake advanced research activities, exploring and expanding the use of disruptive/transformative innovation (AI, ML, etc.) to develop new frameworks and solutions for onboard SAR. Your research can cover a wide range of innovative topics, from the development of novel methods, algorithms and ML pipelines to high-level products;
• contribute to the development and curation of open data sets and tools enabling the community to develop their own AI for applications and research;
• support the definition and implementation of rapid prototyping activities, research sprints and open challenges of innovative EO solutions addressing upcoming lab activities and wider strategy;
• engage with the innovation ecosystem to promote the uptake of new techniques and capture the latest developments in EO and disruptive/transformative innovation;
• publish the research project outcomes in high-impact journals;
• drive collaboration within the Φ-lab community and ESA internal teams to promote the uptake of these new techniques and solutions;
• contribute to the Φ-lab’s strategy, activities and outreach on disruptive technologies for EO;
• maintain a continuous dialogue with the scientific community, including major international programmes and initiatives in the field of AI, ML, SAR and Edge Computing, etc…;
• support Φ-lab’s research network of Young Graduate Trainees, National Trainees, Interns, and Visiting Researchers, as applicable.

Technical competencies

Behavioural competencies

Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward Thinking 

Education

You should have recently completed (within the past five years) or be close to completing a PhD in a relevant field such as data science, AI, Computer Science, Machine Learning, Earth System Science, Climate etc.. with the subject of your thesis being relevant to the description of the tasks outlined above.

Additional requirements

You should also have:
 

•   sound knowledge of themes of interest, such as EO, AI, ML, Edge Computing, ICT revolution technologies in general
•   the ability to think outside the box and explore new avenues, with natural curiosity and a passion for new subjects and research areas
•   experience with one or more general purpose programming languages (e.g. Python) and with general purpose deep learning frameworks (e.g. Tensorflow or PyTorch)
•   the ability to share knowledge with other ESA units
•   knowledge relevant to your field of research, including AI, SAR and edge computing
•   knowledge of SAR signal processing, including raw signals, would be an asset

You should have good interpersonal and communication skills and should be able to work in a multi-cultural environment, both independently and as part of a team.

The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another Member State language would be an asset.

During the interview motivation and overall professional perspective/career goals will also be explored.