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Sd-25110 - R&t Scientist in Machine Learning
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Description
**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.
***:
**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.
**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**
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.).
- 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.
- 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 desig
