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SD-25105 PHD IN SAR-BASED SOIL MOISTURE AND VEGETATION WATER CONTENT ESTIMATION
SD-25105 PHD IN SAR-BASED SOIL MOISTURE AND VEGETATION WATER CONTENT ESTIMATIONLuxembourg Institute of Science and Technology (LIST) • Esch-sur-Alzette, Esch-sur-Alzette, LU
SD-25105 PHD IN SAR-BASED SOIL MOISTURE AND VEGETATION WATER CONTENT ESTIMATION

SD-25105 PHD IN SAR-BASED SOIL MOISTURE AND VEGETATION WATER CONTENT ESTIMATION

Luxembourg Institute of Science and Technology (LIST) • Esch-sur-Alzette, Esch-sur-Alzette, LU
30+ days ago
Job description

Temporary contract | up to 48 months (14+22+12 months) | Belval

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.

To address the urgent societal need for science-based management recommendations for forests under increasing pressure, and to leverage on the fast-developing expertise in multi-disciplinary forest research in Luxembourg, LIST, in collaboration with the University of Luxembourg and the Luxembourg Institute of Socio-Economic Research, has formed a dedicated doctoral training unit (DTU) on “Forest function under stress” (FORFUS). It consists of 4 inter-linked research clusters, focusing on below-ground processes, tree and canopy processes, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems.  See the project website to find out more about the FORFUS doctoral training unit : https : / / www.list.lu / en / research / project / forfus

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

How will you contribute?

Microwave remote sensing measurements are sensitive to the dielectric constant and object geometry. So far, we have used this technology to estimate the vegetation water content (VWC), provide information on the vegetation structure, and estimate the surface soil moisture (SM). It is well known that the canopy penetration depth varies depending on the wavelength, with shorter wavelengths providing information on the top layer of the canopy and longer wavelengths being most sensitive to the characteristics of trunks and soils. Recent research has shown that phase difference between two temporally separated SAR acquisitions is also susceptible to SM, VWC, and atmospheric delay. As a result, the objective of this PhD project is to develop models able to fuse backscattering and phase information to estimate SM and VWC more accurately.

The outcomes of this project will help to better retrieve the soil moisture in the presence of vegetation at high spatial resolution and, at the same time, estimate the plant water content. Automatic and reliable algorithms for estimating the aforementioned parameters on a global scale will enable the implementation of operational services in precision agriculture and forest management. This PhD project will enhance our capacity to comprehend and foresee the resilience and vulnerability of forest ecosystems.

This position is part of the doctoral training unit FORFUS (https : / / www.list.lu / en / research / project / forfus), associated with the FORLUX (https : / / www.list.lu / en / research / project / forlux) research project, both of which together will include 13 doctoral candidates and 4 postdoctoral researchers. We seek candidates with a strong potential to excel in a collaborative and multidisciplinary environment, and use their skill for the benefit of society in the long term.

You will follow the rules and curriculum set out by the Doctoral School in Science and Engineering (https : / / www.uni.lu / research-en / doctoral-education / dsse) and engage in courses and activities organised by the doctoral training unit FORFUS.

Activities of the successful candidate :

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.

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

Education

  • A relevant MSc degree in e.g. engineering, mathematics, physics, remote sensing and machine learning.

Experience and skills

  • Strong interest in modelling, model-data integration, and remote sensing data analysis.
  • Knowledge of programming, remote sensing, and electromagnetism would be an advantage
  • Language skills

  • Proficiency in 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

    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.

    PhD additional conditions :

    Supervisor at LIST : Dr. Marco CHINI

    Work location : Luxembourg Institute of Science and Technology (LIST), BelvaL, Luxembourg

    PhD enrolment : University of Luxembourg, Belval, Luxembourg

    Candidates must be available to start their position in autumn 2025. Please note that university enrolment fees, currently set at 400 EUR per semester (as of July 2025) must be covered by the successful applicant.

    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

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    Phd In Soil Moisture • Esch-sur-Alzette, Esch-sur-Alzette, LU

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