E-2349 Machine Learning Scientist Specialized in

il y a 7 jours

EschsurAlzette, Luxembourg Luxembourg Institute of Science and Technology (LIST) Temps plein

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.

**Responsibilities**:
**You ‘d like to contribute as research support contributor? Join our Environmental Research and Innovation department**:
The Environmental Research and Innovation (ERIN) department of LIST is focusing on pressing environmental challenges our society is facing today. Embedded in the department’s 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. The 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. Its 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. The group further relies on its competences in environmental sciences such as hydrology and hydraulics, meteorology, plant physiology, geography etc. to improve the capacity in monitoring variations of Earth’s biotic and abiotic resources. Moreover, it aims to integrate remotely sensed information with in-situ data, process-based models and leverage on satellite communication, IoT and machine learning technologies in order to provide evidence-based decision support tools in near real time in a variety of thematic domains: disaster risk reduction, precision agriculture/viticulture/forestry, preservation and management of natural resources, maritime surveillance.

**How will you contribute?**:

- You will develop and evaluate Deep Learning models enabling the classification of surface changes using satellite Earth Observation (EO) data. The research will be carried out in the framework of the CHamelEOn project, which aims at developing algorithms based on Artificial Intelligence to detect and interpret surface changes using heterogeneous Earth Observation data. This activity is supported by the Directorate of Defence of the Ministry of Foreign Affairs in Luxembourg.
- You will leverage Artificial Intelligence-based change detection algorithms enabling the synergistic processing and interpretation of heterogeneous data sets. Moreover, the project aims for a high degree of automation and generalization to support evidence-based decision making in the context of natural and man-made disaster management.
- You will exploit both SAR and Optical remote sensing data, as well as deep-learning algorithms to detect relevant changes at different spatial resolutions, ranging from 10 m up to tenths of centimetres. Various satellite data sets will serve as input for this study (e.g., Sentinel-1, Sentinel-2, Planet, Capella).
- 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.

**More specifically, you will contribute to the CH**amel**EO**n** project by**:

- Developing and coding innovative scientific Deep Learning/Machine Learning algorithms to detect surface changes using SAR and optical data (e.g., Generative Adversarial Network (GAN), convolutional neural network aware modules, etc.)
- 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.
- Participation in the drafting of technical reports, scientific articles, patents, and inventions.
- Participation in the implementation of technological solutions (proof-of-concepts, prototypes).

As a part of the Remote sensing and natural resources modelling team, you will participate in the CHamelEOn project which aims at developing algorithms based on Artificial Intelligence to detect surface changes based on heterogeneous Earth Observation data. This activity is supported by the Directorate of Defence of the Ministry of Foreign Affairs in Luxembourg.

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

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

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