E-2437 – PhD CANDIDATE IN FLOODWATER MAPPING USING AI AND EO DATA
Temporary contract 48 months Belvaux
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.
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.
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
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
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
PhD additional conditions:
Supervisor at LIST: Prof. Marco Chini
Work location: Luxembourg Institute of Science and Technology (LIST),
Belvaux, Luxembourg
PhD enrolment: University of Luxembourg, Belval, Luxembourg
Candidates shall be available for starting their position in Q1 2024. Please
note the universities costs are at the charge of the student. Your master
diploma has to be recognized in Luxembourg. Please refer to:
https: // www. uni.lu/en/admissions/diploma-recognition/
https: // guichet.public.lu/fr/citoyens/enseignement-formation/etudes-
superieures/reconnaissance-diplomes.html
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
minimum required Education
Required work experience in years
0 or more years
Job Category
Details
Employment type
Contract type
Hours per week
40
Contract period
Months
Contract duration
48
Location
Country
City
Esch-Sur-Alzette
Recruiter in charge
Carolina DE LEON
Employment type
Full-Time
UO
ERIN
Profile type
Phd Student
