Lunds universitet, Institutionen för naturgeografi och ekosystemvetenskap

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Profile & Tasks
The aim of this project is to implement and evaluate a wood formation model to ultimately give recommendations on how it should be used in the vegetation model, LPJ-GUESS. You will work with tree ring data (e.g. Maximum density, ring width,..) from all over Europe, use and write R functions that handle data from simulations with LPJ-GUESS. You will apply a wood formation model (an R function), in the locations where we have data to compare with observations. The work largely involves data pre-processing to be able to carry out these comparisons – e.g. to first prepare climate data, and then perform simulations with LPJ-GUESS at these locations as input to the wood formation model. It is required that you can do this pre-and post processing yourself, but we will do the necessary implementation in LPJ-GUESS.

Qualifications

  • enrolled to master's education at INES or equivalent education that the employer deems relevant
  • very good English, in speech and writing
  • to be able to solve scientific questions through programming
  • experience with the programming language R, i.e. use or write R functions, visualize complex data, both in time and space.
  • Must understand how to aggregate climate data across time dimensions.
  • Some understanding of tree physiology
  • proof of working independently

Meritorious for the position

  • experience with modifying LPJ-GUESS to change e.g. output.
  • Experience with working on tree rings and climate reconstructions
  • c++
  • solid experience working with geographic data

This employment is set for the time period of 2023-03-20 -2023-07-09 and will be a 25% employment. Rules for employment in Högskoleförordningen (SFS 2017:284), 5 kap 8-12 §§.

Instructions on how to apply

Applications shall be written in English and include a cover letter stating a motivation for why you are interested in the position and in what way the project corresponds to your interests and educational background. In addition to this, an excerpt from LADOK for qualifications are to be attached.

 

Type of employment Temporary position
Contract type Part-time
First day of employment 2023-03-20
Salary Monthely salary
Number of positions 1
Full-time equivalent 25
City Lund
County Skåne län
Country Sweden
Reference number PA2023/672
Contact
  • Annemarie Eckes-Shephard, forskare, +46462224019,annemarie.eckes-shephard@nateko.lu.s
  • Tina Olsson, personalsamordnare, +46462224853,tina.olsson@science.lu.se
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-2229362
  • SACO:Saco-s-rådet vid Lunds universitet, kansli@saco-s.lu.se
  • SEKO: Seko Civil, 046-2229366
Published 03.Mar.2023
Last application date 17.Mar.2023 11:59 PM CET

Return to job vacancies