SD-25105 PHD IN SAR-BASED SOIL MOISTURE AND VEGETATION WATER CONTENT ESTIMATION
ABG-133274 | Master internship | 48 months | Negotiable |
2025-09-02 |

- Engineering sciences
Employer organisation
Website :
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/
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
Description
Temporary contract | up to 48 months (14+22+12 months) | Belval Are you passionate about research? So are we! Come and join us
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.
Profile
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.
Starting date
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