Hydroclimatic Extremes & Causal Pathways Researcher

Newcastle University; Newcastle upon Tyne; On-site; GBP 48,000 - 51,000; Full time

Benefits offered by this job

Generous holiday package

Great pension schemes

Health and wellbeing initiatives

Job summary

Newcastle University is seeking a Senior Research Associate to lead analyses in hydroclimatic extremes and causal pathways within the EXTREME-FUTURES project. The role involves identifying extreme events across scales, exploring interactions between climate drivers and atmospheric features, and developing statistical and AI/ML approaches.

The post collaborates with ETH Zurich, UK Met Office, ECMWF and the broader EXTREME-FUTURES team, contributing to a seamless framework from weather to climate

Qualifications

• PhD in climate science or closely related discipline.
• Experience analysing large observational and reanalysis datasets across multiple scales.
• Strong programming skills in Python or R with reproducible data analysis workflows.
• Experience with statistical analysis, causal inference, weather regimes or related methods is desirable.
• Ability to collaborate with methodological specialists and communicate complex results.

Responsibilities

• Lead analyses within Work Package 1: Causal Pathways.
• Identify extreme temperature and precipitation events across scales and develop AI/ML approaches.
• Collaborate with ETH Zurich, UK Met Office, ECMWF and EXTREME-FUTURES team to deliver WP1 outcomes.
• Present findings at conferences and publish in high‑quality outlets.

Skills

Climate science

Python/R

Statistical analysis

AI/ML methods

Data visualization

Large datasets

Reproducible workflows

Education

PhD in climate science or related field

Job description

Newcastle University is seeking a Senior Research Associate to lead analyses in hydroclimatic extremes and causal pathways within the EXTREME-FUTURES project. The role involves identifying extreme events across scales, exploring interactions between climate drivers and atmospheric features, and developing statistical and AI/ML approaches.

The post collaborates with ETH Zurich, UK Met Office, ECMWF and the broader EXTREME-FUTURES team, contributing to a seamless framework from weather to climate