E-2437 PhD CANDIDATE IN FLOODWATER MAPPING USING AI AND EO DATA

18 Jan 2024
Job Information

Organisation/Company

Luxembourg Institute of Science and Technology

Research Field

Engineering » Computer engineering
Computer science » Other
Mathematics » Mathematical analysis

Researcher Profile

First Stage Researcher (R1)

Country

Luxembourg

Application Deadline

30 Apr 2024 - 00:00 (Europe/Amsterdam)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

40

Offer Starting Date

1 May 2024

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer 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.

Do you want to know more about LIST? Check our website: https://www.list.lu/

Discover our Environmental Research and Innovation department: ERIN Department

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. 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 resources. We integrate remotely sensed information with in-situ data, process-based models and leverage satellite communication, IoT and deep learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, precision agriculture/viticulture/forestry, preservation and management of natural resources, maritime surveillance.

How will you contribute?

In the framework of the FNR-funded SWIFT project "Shallow Water Modelling and Satellite Imagery Combination for Improving Flood Prediction", we aim to advance further our capabilities in flood monitoring and modelling through the integration of remote sensing (RS) observations and shallow water modelling. We intend to leverage our expertise in remote sensing, hydraulic modelling, data assimilation, and data fusion to achieve the project's primary objectives:

• Enhance the retrieval of topography data by combining RS-derived information from diverse satellite missions and geographical datasets.
• Improve the accuracy of RS-based flood extent mapping by enhancing existing algorithms.
• Identify systematic errors in RS-derived flood extent maps and improve algorithms for generating ‘exclusion maps’.
• Enhance flood prediction by assimilating various RS-derived flood observations and leveraging improved topography, flood information, and exclusion maps.

You will:

• Specifically concentrate on the development and validation of novel automated flood mapping systems, based on Synthetic Aperture Radar (SAR) and optical data.
• Further develop a Deep Learning algorithm, designed to detect floodwater in urban areas and over bare soils. A current version of the algorithm uses an urban-aware U-Net model and multi-temporal intensity and coherence data from dual-polarization Sentinel-1. The urban-aware module incorporates a SAR-based probabilistic urban mask to guide the selection of input features crucial for detecting floodwater across specific land cover classes. Our goal is to extend the existing urban-aware module for including vegetated areas, thereby enabling the automated mapping of flooded vegetation.  

• Conduct extensive background literature analysis;
• Plan and organise experiments to define and test hypotheses and develop forefront research;
• Publish the results of the study in peer-reviewed journals;
• Present papers at scientific conferences;
• Take part in the PhD and research training.

Requirements

Research Field

Engineering » Other

Education Level

Master Degree or equivalent

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

Education

A MSc degree in e.g. mathematics, remote sensing, machine learning, engineering, computer science

Experience and skills

Some knowledge of programming and processing of remote sensing data would be an advantage.

Language skills

Good level both written and spoken English.

Specific Requirements

Apply online

 

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

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

Languages

ENGLISH

Level

Excellent

Research Field

Engineering » Other

Years of Research Experience

None

Additional Information
Benefits
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

Eligibility criteria

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

Work Location(s)

Number of offers available

1

Company/Institute

Luxembourg Institute of Science and Technology

Country

Luxembourg

Geofield

Where to apply

Website

https://bit.ly/3HpfjgT

Contact

City

Esch-Belval

Website

http://www.list.lu/

Street

5, avenue des Hauts-Fourneaux

Postal Code

L-4362

E-Mail

[email protected]

STATUS: EXPIRED