SD-25277 MACHINE LEARNING SCIENTIST IN EARTH OBSERVATION DATA APPLICATIONS

24 months - Belvaux-Luxembourg

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 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.

·          Using satellite Earth Observation (EO) data, you will develop and apply methodologies and algorithms for accurate and large-scale monitoring of various phenomena. Your work will embrace both fundamental and applied research projects in areas such as natural disaster mapping (e.g., earthquakes, floods, volcanic eruptions), object classification (e.g., object detection algorithms), and geophysical parameter estimation (e.g., soil moisture).

·          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 exploit both SAR and optical remote sensing data, applying deep learning techniques to estimate surface parameters at spatial resolutions ranging from 10 meters down to a few centimetres (e.g., using Sentinel-1, Sentinel-2, Planet, Capella data).

·          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:

·          Developing and coding innovative scientific Deep Learning/Machine Learning algorithms for many different applications and use cases using SAR and optical data (e.g., GAN, CNN aware modules, diffusion models, transformer, etc.)

·          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 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).

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

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.

·       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.

·          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

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.