Post doctoral fellow in modelling of tropical forest dynamics - Hiring in process/Finished, not possible to apply

How resilient are African tropical forests to a changing climate? How is this affected by tree functional diversity? What drives the functional composition of these forests? We are looking for a fellow to join us in pursuit of answers. In the FunDiCeS project we will combine measurements from the unique Rwanda Tree experiment (www.rwandatree.com) with a state-of-the-art global vegetation model, LPJ-GUESS. LPJ-GUESS is particularly suited to the study of forest dynamics and recent work has substantially upgraded the model’s capability to simulate hydraulic stress. The fellow will improve and apply this upgraded model to investigate how we can better simulate the composition and dynamics of tropical montane forests.

The fellow will work under the supervision of Thomas Pugh and alongside a wider team of researchers working on forest dynamics and ecosystem modelling at Lund University, as well as with project partners at the University of Rwanda and University of Gothenburg, and with the pan-European community developing the LPJ-GUESS model. They will also become part of the BECC research platform, a collaboration between Lund University and the University of Gothenburg, which brings together over 250 researchers working on the topics related to biodiversity and ecosystem services under a changing climate.

 Work duties
The main duties involved in a post-doctoral posistion is to conduct research. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

The fellow will be expected to lead/contribute to research on the topic of tropical forest dynamics, with a focus on forest functional composition, response to drought and tree mortality. The core component of the work is anticipated to be developing and applying a new version of the LPJ-GUESS dynamic global vegetation model which includes a state-of-the-art treatment of plant hydraulics. This will require programming of the LPJ-GUESS model, as well as conducting simulations and analysing both model and field data. The fellow will also contribute more broadly to on-going model development work, particularly related to the simulation of tree mortality and forest dynamics. Tasks will include the development of experimental protocols, carrying out the related simulations and analysis, and leading writing of peer-reviewed papers based on the results. Exact topics and work plans will be agreed in discussion with their supervisor, but the staff member is expected to contribute substantially to the intellectual development of the work. The staff member will also be expected to contribute to or lead applications for external funding as necessary. Only a minor component of teaching is envisaged. Participation in, and/or organisation of, national and international meetings and workshops related to the above is expected, as is carrying out related administration and communication activities. 

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

Additional requirements:

• Very good oral and written proficiency in English.
• Prior experience working with numerical models – preferably vegetation models.
• Documented skills in computer programming, preferably in the C/C++ language family or similar.
• Direct experience of preparing and submitting high-quality scientific publications.
• PhD in natural, biological or physical sciences, or documented substantial knowledge/experience in one or more of these areas in addition to a PhD in another subject.

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.

Additional assessment criteria:

• Knowledge of forest ecosystem processes and their links to the wider Earth System.
• Specialist knowledge in forest dynamics or tree ecophysiology is an advantage, but not essential.
• Experience with environmental modelling, especially ecosystem models such as LPJ-GUESS.
• Competency in computer programming.
• Evidence of ability to develop and execute own research ideas, and act upon own initiative.
• Organisational skills, including ability and willingness to contribute to and coordinate community activities, such as model intercomparisons.
• Emphasis will be placed on the quality and quantity of scientific publications and other academic achievements indicative of emerging independence as a researcher.

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:

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