Internal Research Fellow (PostDoc) in Machine Learning for Earth Observation and Prediction (ML4EOP)

Internal Research Fellowship Opportunity in the Directorate of Earth Observation Programmes.

ESA is an equal opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment. For this purpose, we welcome applications from all qualified candidates irrespective of gender, sexual orientation, ethnicity, beliefs, age, disability or other characteristics. Applications from women are encouraged.

Post
Internal Research Fellow (PostDoc) in Machine Learning for Earth Observation and Prediction (ML4EOP)

This post is classified F2 on the Coordinated Organisations’ salary scale .

Location
ESRIN, Frascati, Italy  

Reporting to the Head of the Explore Office in the ESA Φ-lab, you will work in close cooperation with other staff members of the Directorate of Earth Observation Programmes.
You will be part of the ESA Φ-lab. Our mission is to accelerate the uptake of Earth observation (EO) by embracing innovation and acting as the catalyst for transformative innovation in the sector. Our vision is to become an EO innovation hub, connecting a growing ecosystem of transformative technologies, with artificial intelligence (AI) at its heart. Many challenges with new digital technologies still need to be tackled at scientific, applications and capability level to deliver the maximum value from the EO data provided by satellites for our climate, society and economy. The Φ-lab will bring together early career and senior researchers across multiple disciplines in EO and digital technologies to help develop innovative EO solutions.

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

This research fellowship will be a research opportunity in collaboration with the European Centre for Medium-Range Weather Forecasts (ECMWF). At the end of the two-year stint at ESA, you may have the opportunity to continue your research at the ECMWF as part of the collaboration if the topic and results are deemed valuable.
This forms part of the long-term collaboration between ESA and ECMWF in the field of EO and Numerical Weather Prediction (NWP) and recently ESA and ECMWF joined forces to explore the use of novel methods combining EO data, AI and numerical modelling. As an example, the joint ESA-ECMWF workshop on Machine Learning for Earth System Observation and Prediction [https://www.ml4esop.esa.int] has highlighted the critical need to integrate ML in the prediction pipeline and explore new architectures for scalable, interpretable and physics-informed ML architectures.

In this context, this fellowship will address the use of innovative EO-based solutions to enhance climate resilience by integrating with ML a variety of data types and sources, such as the Internet of Things (IoT), EO and ground-based measurements.

The following themes related to enhancing climate resilience with EO, AI and modelling are of particular interest for the collaboration:

• Improved forecasting of renewable energy production (such as solar) with physics-informed neural networks;
• Live detection and prediction of extreme events (such as floods) with state-of-the-art iterative AI pipelines fusing EO data and modelling capabilities;
• Use of generative AI techniques together with multivariate EO data sets (e.g. Climate Change Initiative) to develop and visualise the new generation of fused EO products supporting climate adaptation.

Within your application, please select one of the above themes and include a short research proposal (of about two pages) on the topic.

In particular, you will:

• undertake advanced research activities exploring the use of state-of-the-art digital techniques such as AI to develop new frameworks to enhance the climate resilience of our society and economy in partnership with wider ESA and ECMWF teams. Research can cover a wide range of innovative topics from the development of novel methods, algorithms and ML iterative pipelines to high-level data fusion products;
• contribute to the development and curation of open data sets and tools enabling the community to develop their own AI for climate resilience 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 uptake of new techniques and capture the latest developments in EO and digital technologies such as AI, blockchain and new computing paradigms;
• publish the research project outcomes in high-impact journals;
• drive collaboration with the AI4EO and global change community, ESA and ECMWF internal teams to promote the uptake of these new techniques and solutions.
  

Knowledge relevant to the field of research

Research/publication record

Ability to conduct research autonomously

Breadth of exposure coming from past and/or current research/activities

Ability to gather and share relevant information

General interest in space and space research

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

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

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

You should also have:

• sound knowledge of themes of interest, such as EO, AI, and climate change adaptation and/or mitigation;
• proven experience in leading research, with international recognition;
• the ability to think outside the box and explore new avenues, with natural curiosity and a passion for new subjects and research areas;
• the ability to work in a multicultural environment as part of a team;
• experience with one or more general-purpose programming languages (e.g. Python) and with general-purpose deep learning frameworks such as Tensorflow or PyTorch;
• the ability to deliver high-quality research and publish in high-level journals.

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.

Other information

For behavioural competencies expected from ESA staff in general, please refer to the ESA Competency Framework .

For further information on the Internal Research Fellowship Programme please visit: Internal Research Fellowship

The Agency may require applicants to undergo selection tests.

In addition to your CV and your motivation letter, please add your proposal of no more than 5 pages outlining your proposed research in the "additional documents" field of the "application information" section.

At the Agency we value diversity and we welcome people with disabilities.  Whenever possible, we seek to accommodate individuals with disabilities by providing the necessary support at the workplace.  The Human Resources Department can also provide assistance during the recruitment process. If you would like to discuss this further please contact us at [email protected] .

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Please note that applications are only considered from nationals of one of the following States: Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Spain, Sweden, Switzerland, and the United Kingdom. Nationals from Latvia, Lithuania, Slovakia and Slovenia, as Associate Member States, or Canada as a Cooperating State, can apply as well as those from Bulgaria, Croatia and Cyprus as European Cooperating States (ECS).

According to the ESA Convention, the recruitment of staff must take into account an adequate distribution of posts among nationals of the ESA Member States*. When short-listing for an interview, priority will first be given to candidates from under-represented Member States *.

In accordance with the European Space Agency’s security procedures and as part of the selection process, successful candidates will be required to undergo basic screening before appointment conducted by an external background screening service. 

*Member States, Associate Members or Cooperating States.