Sd-26092 Postdoc On Vegetation Optimality Modelling In The Presence Of Surface-Atmosphere Feedback

About this position

Temporary contract | 24 months | Belvaux

Are you passionate about research? So are we! Come and join us

The Luxembourg Institute of Science and Technology (LIST) is a leading Research and Technology Organisation (RTO) that drives innovation for the economy and society in Luxembourg and beyond. With cutting-edge expertise in Natural, Built, Industrial environments, Space, AI, Security and defence technologies. LIST bridges scientific excellence and applied research to design solutions that address real-world challenges and create positive impact.

The quality of weather forecasts, seasonal simulations, and climate projections depends critically on the adequate representation of land-atmosphere (L-A) feedbacks. These feedbacks are the result of a highly complex network of processes and variables related to the exchange of momentum, energy, and mass. Significant challenges persist in understanding processes and feedbacks.

The Land-Atmosphere Feedback Initiative (LAFI, https://lafi-dfg.de ) is an interdisciplinary consortium of researchers in Germany and Luxembourg, from atmospheric, agricultural, and soil sciences, bio-geo-physics, hydrology, and neuroinformatics, proposing a novel combination of advanced research methods. The overarching goal of LAFI is to understand and quantify L-A feedbacks via unique synergistic observations and model simulations from the micro-gamma (» 2 m) to the meso-gamma (» 2 km) scales across diurnal to seasonal time scales.

The overall theme of the advertised position is: "Effect of land-atmosphere coupling on vegetation behaviour". The position will build on ongoing experimental and field monitoring work performed by a PhD student at LIST and other researchers in LAFI, and extend the existing Vegetation Optimality Model (VOM, https://vom.readthedocs.io ) to test the following hypotheses:

• Vertical mixing of air increases leaf and canopy water use efficiency;

• Vertical mixing of air reduces plant heat stress (especially during dry periods), i.e., leaf temperatures are lower during periods with enhanced vertical mixing;

• Optimality-based vegetation dynamics and stomatal control improves simulation of transpiration, soil water dynamics and CO2 assimilation compared to conventional parameterization of vegetation and stomatal dynamics.

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

How will you contribute?

You will extend the VOM to simulate wheat and maize crops and consider the effect of L-A coupling strength on the feedbacks between canopy gas and energy exchange and the micrometeorological conditions in the canopy air space.

Crops will be simulated by prescribing known physiological limits of a given crop while allowing plastic plant properties to self-optimise for achieving a maximum net carbon profit.

L-A coupling will be simulated by introducing an explicit air volume representing the canopy air space and replicating the observed coupling between water and CO2 fluxes and concentrations within and above the canopy.

Simulations will be used to assess in how far vertical mixing is beneficial or detrimental for productivity under different environmental conditions (soil moisture, atmosphere) and how it might affect optimal stomatal control at the diurnal time scale. VOM simulations will be compared to simulations by the other models employed in LAFI to assess the potentially added value of optimality principles in improving the simulations of transpiration and ET, and to suggest improvements to the representation of root water uptake and stomatal control in the different models.

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

Education

• You hold a PhD in Physics, Biology, Hydrology, Environmental Science, or a related discipline

Experience and skills

• You have a strong interest for plants, Physics and numerical modelling. A background in plant ecophysiology and/or mass and heat transfer physics would be ideal but is not required.

• You have numerical modelling experience. Experience with the programming language FORTRAN is a plus.

• Knowledge of Python and Git is a plus.

• You have a proven ability to write high-quality scientific papers.

• You like working in a team, explaining and presenting research ideas and results.

Language skills

• Fluency in English (and French), both oral and written. Other relevant languages are 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 60 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 (not remote) and access to Digital lunch vouchers

Apply online

We seek candidates with strong potential to excel in a collaborative and multidisciplinary environment, and use their skills for the benefit of society.

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, ethnicity, 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.

As part of our recruitment process, the selected candidate might be subject to a background check in accordance with applicable laws and institutional policies.

Ideally, candidates shall be available for starting their position in summer 2026. Applications will be reviewed continuously.