Join the ARGOS project team to develop a novel end-to-end AI framework enabling soil moisture estimation from raw SAR data onboard satellites.
Job description
Challenge:
Spaceborne Earth Observation (EO) systems are critical to address Europe’s environmental and security challenges, from climate change monitoring and disaster response to border surveillance and situational awareness. Synthetic Aperture Radar (SAR) satellites are particularly valuable given their ability to capture data independent of weather or lighting conditions. However, the complexity of SAR signals, the computational demands of image formation, and the limited resources of spaceborne platforms hinder the deployment of advanced onboard applications. The ARGOS project aims to overcome these bottlenecks.
Change:
The ARGOS project (Artificial Intelligence for Real-time Guidance of Onboard SAR applications) will develop a novel end-to-end Artificial Intelligence (AI) framework enabling high-level SAR applications directly from raw data onboard satellites. The ARGOS project will design a unified onboard processing chain capable of handling SAR raw data and delivering near real-time application-specific inferences in different fields. To make these processes viable in the constrained space environment, ARGOS will focus on optimizing deep learning models, applying multi-tasking and Tiny AI approaches to reduce computational load and power consumption. The framework will be validated on representative space-qualified hardware, ensuring that the solutions can operate effectively given realistic resources. In parallel, the AI-driven approach will be benchmarked against state-of-the-art onboard SAR processing methods. The project will also demonstrate its versatility through demonstration scenarios, including maritime situational awareness, critical areas identification, and environmental monitoring.
Impact:
ARGOS will advance Europe’s autonomy in intelligent EO capabilities, enabling faster, more efficient, and resilient responses to environmental and geopolitical challenges. Ultimately, the project will bridge the gap between algorithmic innovation and operational deployment, serving both environmental and security needs while reinforcing Europe’s leadership in space-based intelligence.
What you’ll do:
TU Delft will lead the work package focused on the definition and consolidation of the system requirements, onboard applications and demonstration scenarios across a range of application areas. TU Delft will directly define the requirements and consolidate the use cases related to soil moisture estimation. In addition, TU Delft will contribute to the development of the E2E onboard AI framework for soil moisture estimation in applications where real-time response is critical.
You will:
- Generate synthetic and real-world datasets used as input for E2E DL architectures. This will include SAR imagery and derived products.
- Label and structure datasets to support supervised training of E2E AI models.
- Establish a validation and testing strategy for the E2E AI models for soil moisture estimation based on community best practices.
- Validate estimated soil moisture against reference remote sensing datasets and in-situ measurements.
- Be responsible for the curation, storage and maintenance of reference datasets for training and validation of the E2E onboard AI framework for soil moisture estimation.
- Contribute to the definition of the requirements, and consolidation of the use cases related to soil moisture estimation.
- Contribute to reporting and project management, including participation in project meetings and workshops.
- Publish your research results in peer-reviewed publications.
- Present your research outputs in project meetings, workshops, and international conferences.
Where, how and with whom you will work:
You will join the Department of Geoscience and Remote Sensing at TU Delft (Faculty of Civil Engineering and Geosciences) and work closely with Prof. Susan Steele-Dunne, her team at TU Delft (m-wave.tudelft.nl) and international collaborators across the ARGOS project team.
Job requirements
For this postdoctoral role, we are looking for someone with a demonstrated background in SAR with some experience in the use of AI:
- A PhD in Earth Observation, Geodesy or a closely-related field.
- Demonstrated experience with SAR image processing using SNAP, PolSARPro or similar.
- Experience in large-scale validation of EO products against in-situ data would be an asset.
- Demonstrated proficiency with Python or similar scientific programming environment.
- Ability to work with large datasets, develop reproducible workflows and apply modern data science tools.
- Strong organizational skills and a collaborative mindset: the ability to work effectively with international collaborators.
- Excellent communication skills and the ability to write scientific publications independently.
- Good command of written and spoken English.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
Faculty of Civil Engineering and Geosciences
The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions.
CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.
Click here to go to the website of the Faculty of Civil Engineering & Geosciences.
Conditions of employment
- Duration of contract is 1 year.
- A job of 38-40 hours per week.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.
Additional information
For more information about this vacancy, please contact Susan Steele-Dunne (s.c.steele-dunne@tudelft.nl)
Application procedure
Are you interested in this vacancy? Apply via the application button below no later than 25 May 2026 and upload:
- Curriculum Vitae.
- Cover letter, including your motivation for this specific position.
- Transcripts from your MSc/PhD degrees.
- A copy of your PhD thesis will be appreciated.
You can address your application to Prof.dr.ir. Susan Steele-Dunne.
Please note:
- You can apply online. We will not process applications sent by email and/or post.
- As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
- Please do not contact us for unsolicited services.
