Researcher in Physical Geography and Ecosystem Science - Hiring in process/Finished, not possible to apply

Work duties

The researcher shall lead and contribute to research related to development of dynamic global vegetation and soil organic carbon models and application of these to relevant research questions. In the first two years this will focus on two core topics:

1. Develop, apply and evaluate integrated vegetation - soil carbon models for prediction, understanding and quantification of carbon fluxes and greenhouse gas balances in perennial agriculture with special emphasis on deeper soil layers (down to 2 m). These activities are within a framework of an ERC project and a FORMAS project related to quantification and understanding of soil carbon sequestration dynamics in perennial agriculture.
2. Developing and implementing new machine learning-based algorithms within the LPJ-GUESS vegetation model. This includes planning of model developments, training of appropriate algorithms and their coupling into LPJ-GUESS, designing experimental protocols, carrying out the related simulations and analysis. Exact topics and work plans will be agreed in discussion with team members, but there will be a focus on tree mortality and the employee is expected to contribute substantially to the intellectual development of the work. These activities are primarily to be carried out within the context of the Horizon Europe project AI4PEX.

The researcher shall write peer-reviewed papers based on the results. In the longer term they will be required to participate in other relevant projects related to ecosystem model development and application, and are expected to contribute to or lead applications for external funding. Participation in national and international meetings and workshops related to activities is expected, as is carrying out related administration and communication activities. Supporting supervision of a PhD candidate may be included.

Qualifications

Education: PhD in Environmental Science with a specialism in ecosystem modelling.

• Very good oral and written proficiency in English.
• Substantial prior experience developing and applying dynamic global vegetation models, including modelling of soil organic matter, with special reference to LPJ-GUESS.
• Advanced skills in C++ and Python programming.
• At least 6 months of experience in training and applying machine learning models.
• Documented success in leading and contributing to high-quality scientific publications.

Other merits

• Specialist knowledge in plant ecophysiology, soil carbon dynamics and ecological theory.
• Experience in working with high performance computing clusters.
• Strong organisational skills, including ability and willingness to contribute to community activities.
• Emphasis will be placed on academic achievements as evidence of emerging independence as a researcher and the ability to communicate in scientific and outreach contexts.

We will place great emphasis on personal suitability. Consideration will also be given to the potential to develop an independent research career in the future, collaboration skills, how the applicant’s experience and skills complement and strengthen the administrative work within the unit/department, as well as contribute to its future development.

Terms of employment

Permanent employment at 100% of full time. Preferred starting date, 1st February 2024.

For further details contact: thomas.pugh@nateko.lu.se o/a jonas.ardo@nateko.lu.se

Instructions on how to apply

Applications shall be written in English and be compiled into a PDF-file containing:

• an application letter detailing your motivation for this position, a general description of past research work and future research interests (no more than one page),
• résumé/CV, including a list of publications,
• contact information of at least two references,
• copy of certificates/grades that you wish to be considered.

Welcome to apply!