Temporary contract | 24 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, sustainable agri-food systems, terrestrial ecosystems resilience and civil security and defence.

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 damage assessment algorithms caused by natural disasters leveraging advanced machine learning (ML) and deep learning (DL) techniques, alongside very high spatial resolution Earth Observations (EO) data. The research activities will focus on mapping damaged infrastructure such as buildings, bridges, road networks using different types of satellite and sensor data in different ranges of frequencies (optical, radar, etc). 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 collaborate 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/Vision, Remote sensing, image or signal processing, machine learning, applied mathematics, telecommunications engineering or similar disciplines.

Experience and skills

The selected candidate will play a central role in the project. Her/his main mission is to develop a fully automatic and globally scalable deep learning model capable of detecting changes affecting infrastructure using remote sensing, multi-modal, and multi-resolution data. Change detection on multimodal remote sensing images has become an increasingly intriguing and challenging topic in the remote sensing community. The technology plays an essential role in time-sensitive applications, such as disaster response, because it can substantially reduce the time to access the information. Various satellite data sets will serve as input (e.g., Sentinel-1, Sentinel-2, Planet, Capella, Maxar). You will work with an international and highly interdisciplinary team of scientists and engineers with expertise in remote sensing (optical and radar), deep-learning and image classification. The candidate will test the algorithm in a real case scenario in collaboration with project partners.

Required Seniority: 2 years of Post-Doc

Technical Skills:

•     Advanced knowledge of different Deep Learning and Machine Learning algorithms for supervised, unsupervised, and semi-supervised learning.

•     Experience in using and analyzing Earth Observation data (e.g. optical, SAR)

•     Proven previous experience in developing workflows in HPC environment.

•     Good knowledge of EO toolkits (e.g., GDAL, SNAP, EnMAP box, etc.).

•     Excellent programming skills (e.g., Python, C/C++, Matlab, IDL, etc.).

•     Experience in applying Deep Learning and Machine Learning algorithms to different data sets and in particular Earth Observation data for classification, image segmentation and geophysical parameters retrieval (e.g., Sentinel-1 and -2, Worldview, TerraSAR-X, COSMO-SkyMed, etc.).

•     Hands-on experience with at least one of the following popular Machine Learning/Deep Learning frameworks: Scikit-learn, Tensorflow, Pytorch, and Keras.

•     Experience with image processing software.

•     Excellent communication skills in presenting scientific research, and writing papers in scientific journal and technical reports.

•     Communicative and willing to learn, self-organized, and creative.

•     Ability to work both independently and collaboratively in an international team.

Scientific work tasks:

•     Developing and coding innovative scientific Deep Learning/Machine Learning algorithms to detect damaged infrastructures caused by natural disasters using SAR and optical data.

•     Processing and analysing large collections of optical and radar satellite data.

•     Integrating and implementing scientific algorithms on high performance and distributed computing infrastructures to support the development of operational Earth Observation applications, and end-to-end decision support tools.

•     Contributing to the development of partnerships and networks at national and international levels.

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.  

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).

Language skills

·       Good level both written and spoken English

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

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 existing skills and expertise with the requirements mentioned above.