Sd-25277 Machine Learning Scientist in Earth Observation Data Applications

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 conduct research and development activities to enhance the understanding of both natural and human-induced phenomena. The goal is to provide critical information to support the sustainable management of natural resources, mitigate natural disaster impacts, and contribute to civil security. A key focus will be on improving the characterization, monitoring, and understanding of land surface dynamics and changes.
- You will design, train, and evaluate Deep Learning models for object and surface change classification based on satellite EO data. This research will take place within the framework of projects funded by the European Commission, European Space Agency, the National Research Fund of Luxembourg, and other national and international agencies.
- Your work will include the development of AI-based change detection and mapping algorithms that enable the integration and interpretation of multimodal datasets. These projects aim to achieve a high degree of automation and generalization to support evidence-based decision-making processes.
- You will work within an international, multidisciplinary team of scientists and engineers, bringing together expertise in optical and radar remote sensing, deep learning, and image classification.

**More specifically, you will contribute to**:

- Processing and analysing large collections of optical and radar satellite data.
- Contributing to software development, integration, testing and deployment.

**Moreover, you will contribute to the dissemination, valorisation, and transfer of RDI results through**:

- Software licensing.
- Contribute to technical reports, scientific articles, patents, and inventions.
- Contribute to the implementation of technological solutions (proof-of-concepts, prototypes).

**Education**
- You hold a PhD degree in remote sensing, image or signal processing, machine learning, applied mathematics, computer engineering, telecommunications engineering, or computer sciences (or a similar field).

**Experience and skills**
- Good knowledge of EO toolkits (e.g., GDAL, SNAP, EnMAP box, etc.).
- Excellent programming skills (e.g., Python, C/C++, Matlab, IDL, etc.).
- Advanced knowledge of different Deep Learning and Machine Learning algorithms for supervised, unsupervised, and semi-supervised learning.
- 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).
- Experience with image processing software.
- Excellent skills in presenting scientific research, writing papers in scientific journals, and crafting technical reports.
- Communicative and willing to learn, self-organized, and creative.
- Ability to work both independently and collaboratively in an international team.

**Language skills**
- Fluency in English, both oral and written. Other relevant languages are 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
- 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

**Application procedure and conditions**

We kindly request applicants to provide their nationality for statistical purposes