The Biodiversity, Ecology, and Conservation (BEC) Research Group, part of the IIASA Biodiversity and Natural Resources (BNR) Program, is looking for two highly motivated researchers to join two Horizon Europe projects focused on the conservation, restoration, and sustainable management of European ecosystems. One position center on spatial prioritization for integrated land-use planning; the other on statistical and process-based ecological modeling of species and population responses to land management and environmental change
The BEC Research Group develops and applies state-of-the-art ecological knowledge, methods, and tools to understand ecosystem functioning, ecological responses, and feedback within coupled social-economic-ecological systems. The Group applies this knowledge to investigate management options that support sustainability goals with ecological implications.
The BEC Group leads research supporting EU Member States and other countries worldwide in identifying priority areas for habitat conservation, restoration, and sustainable use, in order to achieve national and international area-based conservation targets.
These positions are linked to two Horizon Europe projects:
The Positions:
The selected candidates will work in close collaboration with Dr. Martin Jung, Dr. Lauren Talluto, and Dr. Piero Visconti.
Position 1 - Spatial Prioritization for Land-Use Planning
This researcher will apply spatial prioritization methods for integrated land-use planning at national and continental scale. Candidates with strong literacy in spatial multi-criteria optimization methods, reinforcement learning, or other state-of-the-art spatial planning approaches are of particular interest.
Position 2 - Ecological Modeling of Population Dynamics
This researcher will develop statistical and process-based ecological models simulating spatially dynamic, time-dependent population responses to colonization and population dynamics, as a function of land management (including restoration and conservation actions), species interactions, and other abiotic effects such as climate.
While both researchers will contribute primarily to existing projects and outputs, candidates are encouraged to develop their own research profile within applied ecological and conservation research, in alignment with BEC's research objectives.
Develop workflows for integrated conservation planning using optimization frameworks - (Position 1).
Prepare large (spatial) datasets for spatial planning and assess protected area effectiveness - (Position 1).
Apply and develop ecological modeling approaches to estimate the impact of land-use, climate, restoration, and conservation actions - (Position 2).
For both positions:
Lead the dissemination of project results via high-quality journal publications and conference presentations.
Contribute to the organization of project-related workshops and/or webinars.
Support project partners and other group members in drafting reports and grant proposals.
Develop other scientific outputs as needed.
SKILLS, QUALIFICATIONS AND Experience
PhD, or equivalent experience and qualification, in advanced spatial prioritization and/or ecological modeling, with an interest in developing a career in science.
Strong expertise in at least one scientific coding language (e.g., R, Python, Julia), preferably including scientific software development.
Knowledge of ecological statistics (frequentist and/or Bayesian), particularly spatial statistics and nonlinear models.
Experience handling large, multi-temporal, and multi-resolution spatial datasets, including data harmonization, quality control, and addressing data gaps and uncertainty.
Excellent organizational skills; pro-active and results-oriented, with the capacity to deliver on allocated tasks and respond to deadlines in a timely manner.
Experience working in interdisciplinary teams involving ecologists, remote-sensing scientists, land-system scientists, and environmental decision-makers.
Ability to work independently and as part of an international team distributed across institutions and time zones.
A track record of publishing high-quality scientific research.
Excellent written and oral communication skills in English.
Advantageous:
Experience documenting reproducible analytical workflows and managing code and data using version-control and collaborative development tools.
Experience integrating Earth observation-derived variables (e.g., satellite imagery, aerial imagery, land-cover products) with ecological observations, species-distribution data, ecosystem-condition data, field measurements, or other environmental datasets, using statistical, machine-learning, process-based, or hybrid modelling approaches to analyze ecological patterns and processes.
Knowledge of cloud computing (e.g., Google Earth Engine) and high-performance computing.
Experience developing modelling workflows across more than one scale, from local case studies to continental or global assessments.
Appointment Terms
The successful candidate should be available to take up the position as of 1st October 2026.
The place of work is IIASA in Laxenburg, near Vienna, Austria (home office options available).
The successful candidate will be appointed as a research scholar (R2) in accordance with the IIASA profiles for research careers.
IIASA is committed to a working environment that promotes equality, diversity, tolerance and inclusion within its workforce. This is reflected in our IIASA core values. We encourage qualified candidates from all religious, ethnic, and social backgrounds to apply. In the case that candidates are equally qualified, preference will be given to applicants from countries where IIASA has a Member Organization.
For further information about this opportunity please contact:
VISCONTI Piero - Research Group Leader and Principal Research Scholar (BEC)
For general information about working at IIASA, please contact: recruitment@iiasa.ac.at
In order to apply for this opportunity, you will need to provide the following documents in English:
In order to apply for this opportunity, you will need to provide the following documents in English:
