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 the catalyst for disruptive/transformative innovation in the sector.

Our vision is to become an “EO innovation hub”, connecting EO with a growing ecosystem of disruptive and transformative innovation such as AI, ML, quantum computing or edge computing. 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 contribute to the development of innovative EO solutions.

We offer:

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

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

Field(s) of activity/research for the traineeship

ESA’s Next Generation Gravity Mission (NGGM) and ESA-NASA MAss Change and Geosciences International Constellation (MAGIC) will provide enhanced mass change products at pre-operational level which will contribute to a sustainable approach to water management. These planned missions offer unique hydrological capabilities by monitoring three Essential Climate Variables (ECVs): Terrestrial Water Storage (TWS), Groundwater Storage (GWS) and Anthropogenic Water Use (AWS). NGGM and MAGIC Level-2 and Level-3 simulated products are available from ESA-funded science support activities and are generated by means of realistic fully-fledged simulations during the mission design and implementation phases. Level-2 products are global gravity field products in terms of spherical harmonic coefficients up to a maximum degree and order which depend on the product period. Level-3 products are 1 degree latitude-longitude grid TWS products which typically include additional corrections.

The aim of this fellowship is to perform a multistep approach to enrich our knowledge of the global water cycle and contribute to mitigation strategies related to the water availability crisis.

The steps would include the following:
 

STEP 1: Generate Level-4 NGGM/MAGIC products from Level-2 and Level-3 simulated data through AI-assisted physics-informed data fusion models (supported by other EO data, such as SMOS, SMAP, Sentinel-1 and SWOT).
STEP 2: Decompose the Generated-Level-4 products based on EO products to separate the TWS water column into individual signal components (including groundwater and soil moisture) through AI-based signal processing techniques (such as AI and Fast Fourier Transform).
STEP 3: Integrate Generated-Level-4 products as a component into a Digital Twin (DT) Hydrology for early warning systems to provide additional input for AI-based forecasting models related to extreme events (such as floods and droughts).

In particular, you will:

• undertake advanced research activities exploring and expanding the use of disruptive/transformative innovation such as AI, ML, Quantum Computing, Edge Computing, etc… to  develop new frameworks and  solutions. Research can cover a wide range of innovative topics from the development of novel methods, algorithms and ML iterative 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 a 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 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 fields of AI, ML, Quantum Computing, Edge Computing, etc…;
• support the 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 the themes of interest, such as EO, AI, ML, Quantum Computing, ICT revolution technologies in general, Edge Computing, etc..
• 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 and PyTorch).

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.