Remote Doctoral Researcher: Soil Carbon Modeling

Natural Resources Institute Finland (Luke); Finland; On-site; EUR 55,000 - 58,000; Full time

Benefits offered by this job

Mobile work in Finland

Lunch benefits

Sports, culture or commuting support

Job summary

Natural Resources Institute Finland (Luke) in Helsinki invites a motivated doctoral candidate to join the Academy of Finland’s 4-year DECODE project, modeling ecological interactions in soil organic carbon dynamics. The candidate will develop a Bayesian data assimilation framework built around the Q-model using large datasets and scaling to European level.

The position offers remote work flexibility, strong collaboration with an international team, and doctoral studies through the University of

Qualifications

• Doctoral candidate with strong mathematical skills and interest in ecological modeling.
• Experience with Bayesian inference, MCMC methods, high performance computing or spatial modelling is an asset.
• Good programming skills (e.g., R, Python) and ability to read, write, and debug code independently.
• Knowledge of soil science is not required, but a degree in a relevant field or demonstrated strong expertise in soil science is an asset.
• Good communication skills and ability to work in a multidisciplinary international research team and independently.
• Experience contributing to scientific publications is an asset.

Responsibilities

• Develop a Bayesian data assimilation framework around the Q-model using large datasets (e.g., Holisoils, LUCAS, ICP Forests) and scale results to Europe.
• Integrate diverse data sources, perform model development, and use CSC’s supercomputing infrastructure.
• Publish results in peer‑reviewed journals under supervision of the project’s PI.

Skills

Mathematical skills

Ecological modeling

Bayesian inference

MCMC methods

High performance computing

Spatial modelling

Programming (R, Python)

Education

Higher university degree in a relevant field

Tools

R

Python

Job description

Natural Resources Institute Finland (Luke) in Helsinki invites a motivated doctoral candidate to join the Academy of Finland’s 4-year DECODE project, modeling ecological interactions in soil organic carbon dynamics. The candidate will develop a Bayesian data assimilation framework built around the Q-model using large datasets and scaling to European level.

The position offers remote work flexibility, strong collaboration with an international team, and doctoral studies through the University of