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E-2221 – MACHINE LEARNING - URBAN AREA CLASSIFICATION USING REMOTE SENSING DATA

E-2221 – MACHINE LEARNING - URBAN AREA CLASSIFICATION USING REMOTE SENSING DATA

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. 

https://www.list.lu/


You ‘d like to contribute as a researcher? Join our Environmental Research and Innovation department 

The Environmental Research and Innovation (ERIN) department, made up of 200 life science, environmental science and information technology researchers and engineers, provides the interdisciplinary knowledge, expertise and technologies to lead solutions including the major environmental challenges facing society, such as climate change mitigation, ecosystem resilience, sustainable energy systems, efficient use of renewable resources, and environmental pollution prevention and control.

The department relies on two cutting-edge platforms, the Biotechnologies and Environmental Analytics Platform and the Observatory for the Climate and the Environment, and the GreenTech Innovation Centre (GTIC): a one-stop-shop for the complete development of bio-based products and processes.


Within the ERIN department, the ‘Environmental Sensing and Modelling’ (ENVISION) unit contributes to this mission by carrying out impact-driven research, geared towards monitoring, forecasting and predicting environmental systems in a changing world. An interdisciplinary team of around 50 scientists, engineers, post-docs and PhD candidates is developing new environmental process understanding, alongside new tools and technologies – operating at unprecedented spatial and temporal scales.

Embedded into the ENVISION unit, the ‘Remote sensing and natural resources modelling’ research group capitalizes on a blend of remote sensing data obtained from space- and air-borne platforms, as well as in-situ measured data (collected from heterogeneous IoT devices), for producing information on the status of natural resources for public and private stakeholders.

Responsibilities

How will you contribute?

To strengthen its activities in natural resource modelling and in the development and application of end-to-end decision support tools, LIST is offering a temporary position for a machine leaning scientist specialized in remote sensing applications. 


You will develop and evaluate Machine Learning models enabling the classification of urban areas using satellite Earth Observation (EO) data. The research will be carried out in the framework of the CityWatch project supported by the Luxembourg National Research Fund (FNR) through its JUMP program.


You will leverage SAR and Optical remote sensing data as well as deep-learning algorithms to map buildings at different spatial resolutions, ranging from 10 m up to tenths of centimetres. Various satellite data sets will serve as input (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 CityWatch project by:

  • Developing and coding innovative scientific Deep Learning/Machine Learning algorithms to classify urban areas 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. 
  • 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. 
  • Contributing to the development of partnerships and networks at national and international levels.
  • Contributing to the technical content of new research proposals and commercialisation projects.
  • Disseminating and publishing the results in top ranked scientific journals


Moreover, the appointed candidate 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).


must have requirements

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

Education

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


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 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.


Language skills

  • You are fluent in English (written and oral). Knowledge in at least one of the official languages of Luxembourg (French, German or Luxembourgish) will be considered as an asset. 


We offer

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 such as our Viswall, high-scale incubators and top of the range 3D/4D printings that are part of our toolkit for excelling in all we do;

Multicultural and international work environment with more than 45 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, flexible working hours, 13-month salary, statutory health insurance and access to lunch vouchers; 

Personalized learning programme to foster our staff’s soft and technical skills; 

An environment encouraging curiosity, innovation and entrepreneurship in all areas. 


Apply online

https://www.list.lu/en/jobs/

Your application must include:

  • A motivation letter oriented towards the position and detailing your experience;
  • A scientific CV (which includes a list of the most relevant developed software, and the most relevant projects)
  • Contact details of 2 references.


Application procedure and conditions

  • LIST is an equal opportunity employer and is committed to hiring and retaining diverse personnel. We value all applicants and will consider all competent candidates for employment without regard to national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age or disability; 
  • Applications will be reviewed on an ongoing basis until the position is filled; 
  • An assessment committee will review the applications and select candidates based on guidelines that aim to ensure equal opportunities; 
  • The main criteria for selection will be the correspondence of the existing skills and expertise of the applicant with the requirements mentioned above.

REQUIREDLANGUAGES

To be considered for this position it is crucial that you have knowledge of the following languages
  • Read C1 Advanced
    Write C1 Advanced
    Speak C1 Advanced

OPTIONAL LANGUAGES

The following languages are optional but are considered a plus.
  • Read B2 Upper intermediate
    Write B2 Upper intermediate
    Speak B2 Upper intermediate
  • Read B2 Upper intermediate
    Write B2 Upper intermediate
    Speak B2 Upper intermediate
  • Read B2 Upper intermediate
    Write B2 Upper intermediate
    Speak B2 Upper intermediate
minimum required Education
Required work experience in years
0 or more years
Details
Employment type
Contract type
Hours per week
40
Contract period
Months
Contract duration
12
Location
Country
City
Esch-Sur-Alzette
Profile type
Researcher
UO
Remote sensing and Naturel Resources Modelling
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