Postdoc in Modelling of Forest Vulnerability to Climate Stress - Hiring in process/Finished, not possible to apply

Subject description

Europe’s forests are increasingly under stress from the changing climate. In this project, funded by the Swedish research council, we will identify how vulnerable Swedish forests are to climate stress, to inform forest management to better mitigate risks (WiSdom: Water stress in Swedish forests: identifying risk areas to target management action). Simulating the impacts of climate stress, especially in relation to vulnerability to mortality is still a challenging frontier of research.

As a postdoc in this project, you will develop and apply modelling techniques and model-data fusion, to improve our understanding of drought stress risks in Swedish forests. You will work with data from ICOS stations in Sweden, the flux footprint model FFP, and the LPJ-GUESS forest ecosystem model. The project involves close collaboration with partners from the forest industry, the Swedish Meteorological and Hydrological Institute, and the Swedish Forest Agency. You will become part of the Land surface - Atmosphere Interactions and the ecosystem modelling research groups at Lund University, including a substantial team working on carbon cycle and forest modelling and measurements in Europe and beyond. You will also have the chance to join the BECC and MERGE research communities with many scientists working on topics related to biodiversity, ecosystem services and climate modelling.

Work duties

The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

Based on vegetation information from site inventory, lidar and satellite imagery, you will derive a unique dataset of stand characteristics for the study sites. You will combine these data with flux-tower data and footprint modelling to evaluate and apply the LPJ-GUESS dynamic vegetation model, working with team members currently developing new capabilities to represent drought impact of forests. Tasks will include data analysis, model development and evaluation. We expect you to lead the writing of peer-reviewed papers based on the results.

Detailed description of the work duties:

• Research within the subject area
• Publishing results in high-quality journals
• Attending project meetings and conferences
• Possibilities of teaching and supervision at undergraduate or graduate level
• Possibilities to be involved in applications for additional external funding and to develop own research interests
• Administration related to the work duties listed above.

Qualification requirements

Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, completed no more than three years before the date of employment decision. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

• PhD in Physical Geography, Computational Physics, Forestry, Environmental Science, or a closely related field within Natural Sciences
• Demonstrated proficiency in programming languages: e.g., Matlab, Python, C++ and/or Fortran
• A publication record commensurate with the career stage
• Proficiency in both written and spoken English
• Excellent communication skills, ability to work in a team but also independently, and to complete activities on time.

Assessment criteria and other qualifications

This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers. Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

• A good ability to develop and conduct high quality research.
• Teaching skills.

Merits:

• Subject knowledge relating to forestry, forest ecology, forest ecophysiology
• Excellent knowledge in carbon cycling and greenhouse gas budgeting
• Capacity to develop computer code
• Demonstrated skills in handling and analysis of large datasets
• Experience in numerical analysis and/or geospatial statistics
• Problem solving, organisational and analytical skills

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
This is a full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S and OFR/S, dated 1st February 2022.

Instructions on how to apply

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

• Résumé/CV, including a list of publications
• General description of past research and future research interests (max 2 pages)
• Contact information of at least two references
• Copy of the doctoral degree certificate, and other certificates/grades that you wish to be considered. Please do not send original documents.