Project Assistant in analysis of forest dynamics

Lund University was founded in 1666 and is repeatedly ranked among the worlds top universities. The University has around 46 000 students and 8 500 staff based in Lund Helsingborg and Malmö. We are united in our efforts to understand explain and improve our world and the human condition.

Research and education at the Department of Earth and Environmental Sciences (MGeo) addresses fundamental and applied questions on the Earths past present and future climate and environment including peoples interactions with the natural world and consequences for human wellbeing. MGeo advances and deploys cutting-edge methods models and technologies in environmental science quaternary sciences bedrock geology paleontology physical geography biodiversity and ecosystem science remote sensing Geographic Information Science (GIS) and computational science for health and environment to study processes spanning from the microscopic to the planetary across all time scales.

Work duties

Demographic vegetation models are one of our most advanced and promising tools for understanding how the worlds forests are likely to change in the future. This position will contribute to making us of them in two projects funded under the Horizon Europe programme.

• To have confidence in demographic vegetation model predictions we need to extensively compare them to the AI4PEX project we have assembled a large set of data against which to test such models as well as a set of techniques for this testing. The staff member will carry out analyses benchmarking the simulation outputs from an ensemble of demographic vegetation models from around the world against this dataset.
• In the OBSGESSION project we are applying the LPJ-GUESS demographic vegetation model to explore impacts of disturbances particularly spruce bark beetle on European forests. The staff member will carry out LPJ-GUESS simulations and analyse the results.

Related to both projects they will prepare reports written documentation and code archiving associated with this work and contribute to the writing of a peer-reviewed paper on the topic. This will involve development of analysis code interpretation of outputs and discussion with collaborators globally. Exact details of work plans will be agreed in discussion with the supervisors. Carrying out related administration and communication activities is also expected.

Qualifications

• Education: Masters degree in a quantitative natural science discipline.
• Very good oral and written proficiency in English.
• At least 3 months experience working with data analysis using code-based approaches either from work or from working on a thesis (bachelor or master) from university studies.

Other merits

• Level of skill and experience in data analysis software such as Python R or Matlab.
• Knowledge of forest ecology and dynamics
• Evidence of ability to work independently and act upon own initiative.
• Strong organisational skills including ability and willingness to contribute to community activities.

We will place great emphasis on personal suitability. Consideration will also be given to collaboration skills how the applicants experience and skills complement and strengthen the administrative work within the unit/department as well as contribute to its future development.

Terms of employment

Fixed-term employment (SÄVA) at 100% of full time for a period of 12 months. Preferred starting date as soon as possible.

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 and suitability for this position (no more than one page)
• résumé/CV
• contact information of at least two references
• copy of certificates/grades that you wish to be considered.

Welcome to apply!

Within the Faculty of Science research and education is conducted within Astronomy Biology Physics Geosciences Chemistry Mathematics medical radiation physics physical geography and Environmental Sciences. The Faculty of Science is organized into eight departments gathered in the northern campus area in Lund. The Faculty of Science has approximately 1900 students 330 PhD students and 730 employees.

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