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.
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Education
Experience and skills
Main missions
MUST HAVE
NICE TO HAVE
Scientific work tasks:
Language skills
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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
REQUIREDLANGUAGESTo be considered for this position it is crucial that you have knowledge of the following languages
Write C1 Advanced
Speak C1 Advanced
minimum required Education
Required work experience in years
2 or more years
Job Category
Details
Employment type
Contract type
Hours per week
40
Contract period
Months
Contract duration
18
Location
Country
City
Esch-Sur-Alzette
Contract Type
Fixed Term contract
Employment type
Full-Time
UO
ENVIRONMENT (ERIN)
Profile type
Researcher
Recruiter in charge
Hélène ARAGO