PhD Fellow in Terrestrial Quantitative Ecology

EURAXESS Ireland; Tromsø; On-site; NOK 508,500 - 621,500; Full time

Benefits offered by this job

Flexible working hours

Pension scheme via state fund

Involvement in a cutting-edge research project

Job summary

EURAXESS Ireland is seeking a PhD researcher at UiT The Arctic University of Norway in Tromsø for a three-year full-time position. You will work on ecological forecasts, collaborate with a multidisciplinary team, and contribute to biodiversity conservation.

Qualifications include a Master’s degree in a relevant field and experience with statistical methods. The position offers a gross salary of NOK 565,000 annually, flexible hours, and opportunities for structured PhD training.

Qualifications

• Master’s degree in statistical ecology, statistics with an applied environmental focus, or ecology with a strong quantitative component.
• Experience with statistical methods suitable for spatio‑temporal modelling and forecasting.
• Documented fluency in English.

Responsibilities

• Develop and assess near‑term ecological forecasts.
• Build a coherent framework to link multiple models.
• Collaborate with statisticians and climate scientists.

Skills

Spatiotemporal modelling

Statistical methods

Fluency in English

Bayesian models

Education

Master’s degree in statistical ecology or related field

Job description

Position Overview

UiT The Arctic University of Norway, Department of Arctic and Marine Biology. The Centre for Biodiversity Forecasting (CBF) – part of the Norwegian Research Council’s new sustainable land use centres – is recruiting a PhD researcher (first stage researcher) for a three‑year temporary, full‑time position (37.5 h/week). The residence will be at UiT in Tromsø, with periods spent at the Norwegian University of Science and Technology (NTNU) and other collaborating institutions.

Responsibilities

• Develop and assess near‑term ecological forecasts of Essential Biodiversity Variables (EBVs) through process‑based spatiotemporal modelling, integrating existing single‑species and functional‑group forecasts.
• Build a coherent framework to link multiple models and account for spatial heterogeneity of tundra and subarctic birch forest ecosystems.
• Collaborate with statisticians, quantitative ecologists, climate scientists and managers across NTNU, SINTEF, Nord University, NINA, Met and NPI.
• Participate in field work, data collection and adaptive monitoring to iteratively improve models.
• Work in an interdisciplinary setting, combining environmental science, statistics and ecology to address biodiversity conservation, reindeer husbandry, harvesting and renewable energy under changing land‑use and climate conditions.

Qualifications

• Master’s degree in statistical ecology, statistics with an applied environmental focus, or ecology with a strong quantitative component.
• Experience with statistical methods suitable for spatio‑temporal modelling and forecasting.
• Documented fluency in English (Nordic applicants may attach a high‑school diploma).

• Familiarity with integrative modelling approaches that combine diverse information sources.
• Practical experience with Bayesian models.
• Working knowledge of Norwegian or another Scandinavian language.

Benefits

• Involvement in a cutting‑edge research project with an international, multidisciplinary team.
• A self‑contained academic environment supported by dedicated colleagues and a state‑collective pay agreement.
• Flexible working hours, pension scheme via the state pension fund and a gross annual salary of NOK 565 000 (full time) in accordance with State salary scale code 1017.
• Opportunity for structured PhD training with provisional admission to UiT’s PhD programme.

Inclusion & Diversity

UiT The Arctic University of Norway actively promotes equality, gender balance and diversity among employees and students and strives to create an inclusive and safe working environment. All qualified applicants, including those with disabilities, gaps in their CV or immigrant backgrounds, are encouraged to apply. Where a candidate meets the minimum qualifications, UiT will adapt working conditions to meet accessibility needs.