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Selected role

DC-26094- POSTDOC/DATA SCIENTIST - AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR FLASH FLOODS

Luxembourg Institute of Science and Technology (LIST) Esch-sur-Alzette, L0L, LU

Senior Full-time

Description

**Temporary contract | 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 leading Research and Technology Organization (RTO) that drives innovation for the economy and society in Luxembourg and beyond. With cutting-edge expertise in Natural, Built, Industrial environments, Space, AI, Security and defence technologies. LIST bridges scientific excellence and applied research to design solutions that address real-world challenges and create positive impact.

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

How will you contribute?

You will be part of LIST’s Remote sensing and natural resources modelling group

Embedded in the Environmental Sensing and Modelling (ENVISION) unit, the Remote sensing and natural resources modelling 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 in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems, terrestrial ecosystem resilience, civil security and defence.

To strengthen its activities in supporting humanitarian anticipatory actions with AI-based methods, LIST is offering a 18-month fixed-term postdoctoral/data scientist position in AI-driven climate risk modelling and early warning systems. The successful candidate will join a collaborative team of scientists within the Remote Sensing and Natural Resources Modeling (REMOTE) group at LIST in Luxembourg. The researcher will work closely with remote sensing experts, machine learning scientists and hydrologists on the development and refinement of AI-based early warning triggers for flash floods.

The successful applicant will contribute to the AIGLE project by:

Developing innovative scientific Deep Learning/Machine Learning algorithms for flash flood forecasting.
Contributing to the collection, assessment, and integration of diverse data sources (e.g. rainfall forecasts, topography, land use, and infrastructure) relevant to flood risk modelling.
Testing ML/AI models to evaluate and improve the accuracy, reliability, and lead time of flash flood early warnings across different geographic and climatic contexts.
Integrating and implementing scientific algorithms on high performance and distributed computing infrastructures to support the development of operational applications, and end-to-end decision support tools.
Contributing to software development, integration, testing and deployment.
Engaging with stakeholders, including humanitarian partners, meteorological services, and regional/national and local authorities, to support data sharing, capacity building, and trust in AI-derived alerts.

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

Education**

PhD degree in Remote sensing and geoscience, Atmospheric sciences, Environmental and climate sciences, Geomatic sciences, Earth science, Hydrology, Machine learning, Applied mathematics, or a closely related field

Experience and skills

At least three years of experience in remote sensing, meteorology, hydrology or closely related field
Good knowledge of EO toolkits (e.g., GDAL, Xarray, SNAP, EnMAP box, etc.).
Advanced knowledge of different Deep Learning and Machine Learning algorithms for supervised, unsupervised, and semi-supervised learning and/or time-series forecasting.
Hands-on experience with at least one of the following popular Machine Learning/Deep Learning frameworks: Scikit-learn, Tensorflow, Pytorch, and Keras.
Knowledge of advanced statistical methods to evaluate Machine Learning models.
Experience with distributed cloud storage systems and cloud computing services.
Experience in HPC (including heterogeneous architectures).
Strong interpersonal and communication skills and the ability to work both independently and collaboratively with researchers, humanitarian workers, and other colleagues from different scientific backgrounds.
Strong statistical and computer skills including demonstrated proficiency with computer coding, such as Python, MATLAB, R, and expertise in statistical modelling.
Experience in designing, planning, and conducting experimental procedures, including the ability to meet project goals in a timely manner, and follow through on project deliverables.
Excellent technical, analytical, organizational, and problem-solving skills. Strong attention to detail, and meticulous work style, as evidenced by previous research.

Language skills

Excellent English (oral and written) is mandatory.

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 meters, 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 fulfill 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

*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 2-3 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 existing skills and expertise with the requirements mentioned above.

Languages English Education Doctorate Experience 3+ years

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