SD-25106 – PHD STUDENT IN REMOTE SENSING OF FOREST STRESS

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

Temporary contract | 14+22+12 months | Belvaux Are you passionate about research? So are we! Come and join us

How will you contribute? 

The doctoral candidate will develop and apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed to enable the extraction of spatiotemporal information from time-series optical data with a focus on years with pronounced forest stress occurrence. The accuracy of the forest trait retrieval method will be evaluated against drone, field and lab data collected at experimental sites. The developed method will be applied to satellite data (Sentinel-2, PRISMA, EnMAP) over forests in the Greater Region (e.g., the National Park Hunsrück Hochwald) and the resulting trait maps will be analysed together with available forest disturbance databases and geospatial data layers.

You will be mainly in charge of:

• Processing multi- and hyperspectral satellite and drone data
• Collection of field data on relevant forest traits and laboratory analysis
• Forest radiative transfer modelling
• Hybrid model inversion including machine and deep learning methods
• Publications in peer-reviewed journals

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.

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

Education

• M.Sc. degree in remote sensing, environmental sciences, geography, geophysics, geoinformatics, or related

Experience and skills

• Multi- and hyperspectral images processing
• Knowledge of quantitative remote sensing
• Knowledge of physical and statistical modelling concepts
• Programming skills in Matlab, R, and/or Python
• Experience in the organisation of field campaigns

Language skills

• Fluency in English, both oral and written.