Research Assistant in Remote Sensing – Luke Finland

About Position/Job

Natural Resources Institute Finland (Luke) is recruiting a Research Assistant in Remote Sensing to support advanced research on forest and peatland biodiversity and ecological restoration in Finland. This full-time, temporary position is embedded within nationally significant research activities and closely linked to the EU-aligned FORbEST project, focusing on identifying and mapping biodiversity-rich forests. The role involves working with remote sensing technologies, geospatial analysis, machine learning, and biodiversity datasets to model species diversity and generate high-impact ecological maps. Supervised by Dr Parvez Rana (Senior Scientist), the position offers strong academic value through interdisciplinary methods, international collaboration, and potential fieldwork. The role is ideal for early-career researchers seeking hands-on experience in environmental science, forestry, ecology, and spatial data science, while contributing to evidence-based conservation and restoration strategies.

Position/Job Details

Position: Research Assistant
Institution: Natural Resources Institute Finland (Luke)
Department: Not specified
Research Field: Remote Sensing, Biodiversity, Ecology
Location: Helsinki, Finland
Number of Posts: 1
Job Type: Full-time, Temporary
Start Date (Anticipated): 2026
Working Hours: Full-time
Salary Range: Not specified
Required Degree/Diploma: Master

Research Area

Forest biodiversity
Peatland ecosystems
Remote sensing and geospatial analysis
Machine learning for ecological modelling
Species richness mapping

Eligibility & Qualifications

Minimum Requirements:

Background in remote sensing or geospatial sciences
Proficiency in R, Python, and ArcGIS
Good command of written and spoken English
Master’s degree completed or near completion in a relevant field

Preferred Qualifications:

Knowledge of forest and peatland biodiversity
Experience with GBIF, European Vegetation Archive, or similar datasets
Familiarity with machine learning applications in environmental science

Key Responsibilities

Analyse satellite imagery, LiDAR, and drone data
Process and interpret biodiversity datasets
Support machine learning models for predicting biodiversity-rich forests
Produce maps of species richness and biodiversity hotspots
Collaborate with international partners within the FORbEST project
Assist with project coordination and potential fieldwork

Application Process

How to Apply

Applications should preferably be submitted online via the official government recruitment platform. Postal or email applications are accepted if clearly marked with the position ID and submitted before the deadline.