Temporary contract | up to 18 months | Belvaux

Are you passionate about research? So are we! Come and join us

The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

Do you want to know more about LIST? Check our website: https://www.list.lu/

How will you contribute?

You will be part of the Remote Sensing and Natural Resources Modelling (REMOTE) group of LIST. Embedded in the Environmental Sensing and Modelling (ENVISION) unit, the ‘group is carrying out impact-driven research, geared towards monitoring and predicting environmental systems in a changing world. Our research group capitalizes on a blend of remote sensing data obtained from space- and air-borne platforms, as well as in-situ data measured with Internet of Things (IoT) devices, for producing information on the status of natural resources. Our research and development activities focus on the synergistic use, processing, and interpretation of data from multiple complementary active and passive sensors installed on both space- and airborne platforms. We rely on competences in environmental sciences, such as hydrology and hydraulics, meteorology, plant physiology, and geography for monitoring variations in Earth’s biotic and abiotic resources. We integrate remotely sensed information with in-situ data, process-based models and leverage satellite communication, IoT and machine learning technologies to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, precision agriculture/viticulture/forestry, preservation and management of natural resources, maritime surveillance.

The researcher will contribute to an emergency response project, funded by the Ministry of Foreign and European Affairs, Defence, Development Cooperation, and Foreign Trade of Luxembourg. This initiative is part of a collaboration between the World Food Programme (WFP) Innovation Accelerator, CERN, and LIST. The collaboration aims to identify, support, and implement high-impact innovations aligned with achieving the Sustainable Development Goal of Zero Hunger.

One of the project's key objectives is to develop a crop yield forecasting tool leveraging advanced machine learning (ML) and deep learning (DL) techniques, alongside cutting-edge Earth Observations (EOs). The proposed forecasting system will follow a modular and scalable design, facilitating the integration of multiple EO data streams and enabling applications at various scales, from fine-scale (e.g., field-level) to coarse-scale (e.g., country-level).To address this challenge, the project will employ a range of ML/DL techniques, such as XGBoost, LightGBM, and Bayesian Neural Networks. These models will use meteorological and EO data streams as predictors, with national and regional crop yield statistics as target variables. Additionally, the ML/DL models will incorporate data generated from a physically based crop growth model to enhance accuracy and robustness. The selected candidate will join the Remote Sensing and Natural Resources Modelling (REMOTE) group within the Environmental Sensing and Modelling (ENVISION) RDI unit. She/He will closely collaborates with the project's partners, including the WFP officers in the targeted countries.

Is Your profile described below? Are you our future colleague? Apply now!

Education

•  PhD degree in Computer Science, Environmental Science, or similar disciplines   

Experience and skills

Main missions

• The selected candidate will play a central role in the project and its outputs. Her/his main mission is to develop a data-driven crop yield forecasting tool capable of delivering in-season probability information on potential crop yield anomaly and quantity estimation. In a first step, the tool will be tested for targeted geographical areas and specific crop types at province and country level. 
• Required Seniority: 2 years of Post-Doc
• Technical Skills: Advanced Statistics and Machine Learning Techniques, EOs, Crop modelling, High Performance Computing

MUST HAVE

• Extensive knowledge of machine learning and deep learning techniques
• Experience in manipulating and analyzing Earth Observation data
• Advanced statistics and uncertainty quantification
• High proficiency in high-level scripting languages (e.g., Python)
• Proven previous experience in developing workflows in HPC environment.

NICE TO HAVE

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• Experience with land surface and crop growth modelling
• Knowledge of post-processing techniques of weather forecast products
• Proven knowledge of crop growth model setup and calibration

Scientific work tasks:

• Develop workflow to ingest multiple EO data streams into ML/DL techniques.
• Identify skillful predictors of crop yield forecast at different lead time
• Generate crop yield forecasts at different lead time for the selected case studies of the project.
• Perform robust uncertainty analysis and anomaly outlooks of crop yield forecasts.
• Integrate additional data streams generated by a crop growth model for training ML/DL techniques

Language skills

• Flawless knowledge of English (both spoken and written) is required.
• Knowledge of German and/or French and/or Luxembourgish is considered as an asset.

Your LIST benefits

• An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
• Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
• Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
• An environment encouraging curiosity, innovation and entrepreneurship in all areas
• Personalized learning programme to foster our staff’s soft and technical skills
• Multicultural and international work environment with more than 50 nationalities represented in our workforce
• Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
• Gender-friendly environment with multiple actions to attract, develop and retain women in science
• 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
• Flexible working hours, home working policy and access to lunch vouchers

Project management tasks:

• Establish a continuous communication and effective collaboration with the partners of the project.
• Assist in the preparation of project reports and presentations in project meetings.
• Participate actively in the maintenance of a project-dedicated version-control system (e.g., GitLab).
• Explore and employ cutting edge software packages facilitating the interoperability and reusability of the data generated in the project.  
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Dissemination, valorisation and transfer tasks:

• Contribute to dissemination, valorisation and transfer of project results (e.g., participation in scientific conferences, exhibition of technology, training sessions, drafting of technical reports, and publication in reputed peer-reviewed scientific journals).
• Participation in the implementation of technological solutions (proof-of-concepts, prototypes).

Apply online

Your application must include:

• A motivation letter oriented towards the position and detailing your experience
• A scientific CV with contact details
• List of publications (and patents, if applicable)
• Contact details of 2 references

Please apply ONLINE formally through the HR system. Applications by email will not be considered.

Application procedure and conditions

We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.

LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.

Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be the alignment of the applicant's