E-2413 - Researcher in Crop Modelling

il y a 3 semaines

EschsurAlzette, Luxembourg Luxembourg Institute of Science and Technology (LIST) Temps plein

**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.
- Discover our Environmental Research and Innovation department: ERIN Department

**How will you contribute?**:
You will be involved in the framework of the HERITAGE (High-resolution crop yield forecast based on Earth Observations, machine learning, and crop modelling) project funded by the Luxembourg National Research Fund (FNR).

The project targets the development of a prototyped forecasting tool that leverages efficient machine learning techniques, cutting-edge advancements in Earth Observations (EOs), and process-based crop modelling. The envisioned forecasting system will adopt a modular and scalable approach, enabling the easy integration of multiple EO data streams and serving, in the longer term, to a wider range of both fine

To address this challenge, the HERITAGE project will make joint use of the most recent version of the Community Terrestrial Systems Model (CTSM), multiple EO data sets, and national/regional crop yield statistics.

You will be incorporated in the Remote Sensing and Natural Resources Modelling (REMOTE) group of the Environmental Sensing and Modelling (ENVISION) RDI unit and will closely collaborate with the project’s private partner operating the Data Centre of the Luxembourg Space Agency and with the national HPC organization in charge of the long-term operation of Luxembourg’s supercomputer MeluXina.

You will play a central role in the project and its outputs. Your main mission is to improve the physiological parameterization of the crop module of CTSM, to develop a framework to perform a robust uncertainty analysis, and to generate a dataset that will be used to train a machine learning algorithm. To address these challenging tasks, you will be asked to explore the use of advanced statistical (e.g., perturbed parameter ensemble) and machine learning (e.g., neural networks emulator) techniques.

**Education**:

- PhD degree in Environmental Science, Crop Science, or similar disciplines

Experience and skills:
**Technical Skills: Crop modelling, High Performance Computing, Advanced Statistics and Machine Learning Techniques. Seniority needed of 2 years of Post-Doc experience.**

**MUST HAVE**
- Proven previous experience in crop modelling and/or Land Surface Models.
- Proven knowledge of model calibration and uncertainty assessment
- Knowledge of machine learning techniques
- High proficiency in high-level scripting languages (e.g., Python)
- Proven previous experience in developing workflows in HPC environment.
- Experience in manipulating and analysing Earth Observation data

**NICE TO HAVE**
- Experience with CTSM land surface model
- Knowledge of post-processing techniques of weather forecast products

**Language skills**
- Flawless knowledge of English (both spoken and written) is required.
- Knowledge of German and/or French and/or Luxembourgish is considered as an asset.

**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
- 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**
- Applications will be reviewed on an ongoing basis until the position is filled
- The main criteria for selection will be the correspondence of the existing skills and expertise of the applicant with the requirements mentioned above

**REQUIRED**LANGUAGES**:
To be considered for this position it is crucial that you have knowledge of the following languages

**Engl

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