The European Space Agency is seeking an Internal Research Fellow in Machine Learning for Earth Observation and Prediction (ML4EOP) for the Directorate of Earth Observation Programmes. This fellowship is classified as F2 on the Coordinated Organisations’ salary scale and will be based in ESRIN, Frascati, Italy, in collaboration with the European Centre for Medium-Range Weather Forecasts (ECMWF).
The ESA offers relocation support for successful candidates. Accepting job applications for a position from individuals who are nationals of certain countries in Europe, including 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. However, nationals from Latvia, Lithuania, Slovakia, and Slovenia can also apply as Associate Member States, and Canada can apply as a Cooperating State. Additionally, Bulgaria and Cyprus can apply as European Cooperating States (ECS).
Job Req ID: 17561
Closing Date: 12 May 2023 23:59 CET/CEST
Vacancy Type: Internal Research Fellow
Location: ESRIN, Frascati, Italy
The 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 members of the Directorate of Earth Observation Programmes.
You will be part of the ESA Φ-lab. The mission will be to accelerate the uptake of Earth observation (EO) by embracing innovation and acting as the catalyst for transformative innovation in the sector. The 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 levels 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.
Field(s) of activity/research for the traineeship
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 Ph.D. within the past five years. In particular, the following is required for this position:
a Ph.D. 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.
For more information, please click here and Apply.
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