Internal Research Fellow (PostDoc) in AI for Climate Adaptation, Resilience, and Mitigation

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 and in particular with the Actionable Climate Information Section.

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 EO with a growing ecosystem of disruptive and transformative innovation, encompassing AI, ML, quantum computing, edge computing, metamaterials, photonics, etc.. Many of the challenges posed by new technologies still need to be tackled at the scientific, application and capability levels to deliver the 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 develop innovative EO solutions.

We offer:

• a stimulating multinational, interdisciplinary and 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 challenges;
• the freedom and focus you need to conduct creative research while making an impact on ESA’s strategy;
• a wide network of relationships and collaboration with top academia, industry and research centres;
• the opportunity 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

This fellowship aims to explore the use of space and ground-based EO products integrated with disruptive technologies to address climate adaptation, resilience and/or mitigation. For example:

• investigate how AI can be used to enhance EO for planning, implementing and monitoring climate adaptation and/or mitigation actions, including attributing any resulting changes from these actions;
• consider and assess relevant climate change metrics or indicators for the above point;
• design AI pipelines that fuse EO data and climate scenarios/projections (e.g., CMIP, CORDEX, DestinE Digital Twin for Climate Change Adaptation) to support decision-making frameworks for relevant sectors (e.g. European Commission’s Climate Action and the Green Deal);
• explore explainable AI techniques to enhance transparency or uncertainty propagation through the pipeline process;
• investigate which EO data can be most suitable for different climate adaptation/mitigation situations (e.g. required spatial and temporal resolutions);
• possible focus topics could include the urban environment, agriculture, health or adaptation to climate extremes (heatwaves, flooding, wildfires, droughts, storms and storm surges, etc.).

Within your application, please provide a research proposal (no more than five pages) answering the following questions:

• What is the climate adaptation/resilience/mitigation research problem you would like to address?
• Which is your chosen disruptive technology?
• What is your planned method to address your research question?
• Why is this research proposal important to society?

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In particular, you will:

• undertake advanced research activities exploring and expanding the use of disruptive and transformative innovation such as AI, ML, quantum computing and edge computing to develop new frameworks and solutions. Research may cover a wide range of innovative topics:
  • exploration of innovative methodologies and technologies;
  • development of novel methods, new technology implementations, (e.g. ML models) and/or high-level products;
  • contribution to the development and curation of open data sets and tools enabling the community to develop its 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 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;
• support the Φ-lab’s daily activities and research network of ESA Graduate Trainees, National Trainees, Interns and Visiting Researchers, as applicable;
• develop and evaluate AI/ML models to identify, quantify and predict climate change impacts relevant to adaptation, resilience and mitigation on the topics identified above;
• integrate multisource EO data (e.g. Sentinel missions, ESA Climate Change Initiative – CCI), including ESA third-party missions, climate reanalyses (e.g. ERA5 from the Copernicus Climate Change Service) and climate projections (DestinE Digital Twin for Climate Change Adaptation, CMIP and/or CORDEX data);
• contribute to climate adaptation, resilience and mitigation as well as digital twin activities, including Φ-lab’s collaborations with the Climate Change Initiative, Destination Earth, ESA Digital Twin Earth, and Copernicus programmes;
• ensure solid scientific content for climate adaptation, reliance and mitigation.

Technical competencies

Behavioural competencies

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

For more information, please refer to ESA Core Behavioural Competencies guidebook

Education

You should have recently completed, or be close to completion of a PhD in a related technical or scientific discipline. Preference will be given to applications submitted by candidates within five years of receiving their PhD. In particular for this position, the following is required:

PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science, climate etc. with a thesis subject relevant to the description of the tasks outlined above.

Additional requirements

In addition to your CV and your motivation letter, please prepare a research proposal of no more than 5 pages. This proposal should be uploaded to the "additional documents" field of the "application information" section.

You should have:

• Sound knowledge of themes of interest, such as EO, AI, ML, quantum computing, ICT revolution technologies and edge computing;
• 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, for example Python, and general purpose deep learning frameworks, such as Tensorflow or PyTorch;
• The interest and ability to share knowledge with other ESA organisational units.

You should also 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. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process.