Research Associate (Statistical Population Ecology) in Sheffield

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world‑class university.

We offer a range of benefits, including 41 days annual leave (pro‑rata) with the option to purchase more, flexible/hybrid working, a generous pension scheme, a wide range of retail discounts, and support for staff wellbeing.

Overview

We are seeking a highly motivated and quantitatively skilled Research Associate to join an exciting NERC‑funded project, ‘Harnessing Ensemble Models for Robust Near‑Term Population Forecasts under Environmental Change’. The successful candidate will develop and apply ensemble modelling approaches that integrate multiple sources of ecological information to improve predictive performance.

Main Duties And Responsibilities

• Develop, implement and evaluate statistical and computational models for near‑term population forecasting, including time‑series (e.g. state‑space/MARSS) and demographic (e.g. IPM/MPM) approaches.
• Design and test ensemble modelling frameworks, including hierarchical/meta‑model approaches for combining forecasts.
• Conduct simulation studies to evaluate forecasting performance across ecological and data scenarios.
• Analyse complex ecological datasets, including experimental microcosm data and long‑term field datasets.
• Contribute to the development of robust, reproducible analytical pipelines in R (or similar environments).
• Integrate work across simulation, experimental and real‑world applications to assess model performance under different sources of uncertainty.
• Contribute to the application of forecasting approaches to long‑term population datasets (e.g. Soay sheep).

Dissemination and Outputs

• Publish research findings in high‑quality peer‑reviewed journals.
• Present results at national and international conferences and project meetings.
• Contribute to the development of open‑source tools, codebases and documentation to support uptake of forecasting methods.

Collaboration and Project Contribution

• Work collaboratively with project partners across institutions and disciplines.
• Contribute to project meetings, workshops and synthesis activities.
• Engage with non‑academic stakeholders (e.g. conservation organisations) to support the development of tools and outputs.

Wider Contributions

• Support the supervision of postgraduate research students where appropriate.
• Maintain high standards of data management, documentation and research integrity.
• Carry out other duties commensurate with the grade and remit of the post.

Person Specification

We welcome applications from all candidates with strong quantitative expertise relevant to this role. We are particularly interested in applicants from ecological, statistical, mathematical or closely related disciplines who can bring rigorous analytical approaches to population forecasting under environmental change.

Criteria

• Essential: PhD (or equivalent) in a relevant discipline such as quantitative ecology or statistics.
• Essential: Strong quantitative and analytical skills with experience applying statistical approaches to ecological or environmental data.
• Essential: Experience with relevant modelling approaches such as time‑series methods or demographic projection models.
• Essential: Experience using programming tools for data analysis (e.g. R, Stan or similar) with an emphasis on reproducible workflows.
• Essential: Experience contributing to shared code or research databases, including version control.
• Essential: Strong problem‑solving skills, particularly with uncertain, noisy or incomplete data.
• Essential: Effective written and verbal communication skills, including the ability to present complex ideas clearly.
• Essential: Evidence of producing, or potential to produce, high‑quality research outputs (publications, preprints, reports).
• Essential: Good organisational and time‑management skills, with the ability to manage multiple priorities and meet deadlines.
• Essential: Commitment to high standards of research practice, including data management, documentation and reproducibility.
• Desirable: Experience engaging with applied or stakeholder‑relevant research, including translating research outputs for non‑academic users.
• Desirable: Ability to design, implement and deliver independent research contributing to a broader collaborative project.

Further Information

Grade: 7
Salary: £38,784 – £39,906 per annum
Work arrangement: Full‑time (100 % FTE)
Duration: Fixed‑term, available from 1 July 2026 for 36 months
Line manager: Professor of Population Ecology

EEO Statement

We are a Disability Confident Leader. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.