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Sd-25106 - Phd Student in Remote Sensing of Forest Stress

il y a 2 semaines


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**SD-25106 - PHD STUDENT IN REMOTE SENSING OF FOREST STRESS**:

- Réf **ABG-133285**
- Stage master 2 / Ingénieur
- Durée 48 mois
- Salaire net mensuel Negotiable
- 02/09/2025
- Luxembourg Institute of Science and Technology
- Lieu de travail- Luxembourg
- Champs scientifiques- Sciences de l’ingénieur

**Établissement recruteur**:
**Site web**:
**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.

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

**How will you contribute?**

**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

**Profil**:
**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.

**Prise de fonction**:

- Dès que possible