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JG Graham

4 months ago

Predicting Future Climate and Compound Stressors for Intertidal Habitats: A Multidisciplinary PhD Project University of the Highlands and Islands in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

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Country

United Kingdom

University

University of the Highlands and Islands

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Keywords

Computer Science
Ecology
Environmental Science
Biology
Mathematics
Statistical Analysis
Marine Biology
Earth Science
Oceanography
Science Communication
Big Data
Atmospheric Dynamics
Climate Dynamics
Coastal Ecology
Computational Modelling
Field Experimentation
Statistical Modelling
Climate Variability
Statistic
Machine learning

About this position

This PhD project at the University of the Highlands and Islands, based at the Scottish Association for Marine Science (SAMS-UHI), aims to advance our understanding of the intertidal zone—one of the planet’s most stressed and vulnerable habitats. Intertidal species face multiple, compounding stressors including warming seas, rising sea levels, and changing storm patterns. Current climate models, both terrestrial and marine, struggle to accurately represent the complex processes fundamental to these habitats. Supported by a multidisciplinary supervisory team with expertise in physical and ecological processes, and using both models and observations, the project seeks to improve future climate projections and enable better management of intertidal habitats under climate change.

The student will benefit from additional supervision from Dr Oliver Andrews (University of York) and Prof Peter Robins (Bangor University), and will have opportunities to collaborate with the Scottish Government and UK Met Office, providing a direct route for research outputs to inform policy and advice across the UK. The project offers a unique opportunity to develop technical skills in observational sampling (field work), coding for big data analysis, and coastal climate modelling. Students will gain interdisciplinary expertise in coastal ocean dynamics, land-ocean-atmosphere interactions, interacting climate extremes, ecology of coastal habitats, and science communication. Training opportunities include bitesize sessions on effective communication and teaching, as well as access to taught courses from the SAMS-UHI undergraduate programme if needed.

The project is novel in its multidisciplinary approach, combining observational data sampling and analysis with both physical and ecological models, including machine learning techniques. It is timely, coinciding with the publication of the UK’s Fourth Climate Change Risk Assessment (CCRA4) and the next generation of regional ocean climate projections. The student will engage with stakeholder partners and international networks to help inform future climate policy advice. The real-life challenge addressed is the threat climate change poses to intertidal habitats, combining impacts from the atmosphere, ocean, and land surface.

The project will improve predictions of future changes and climate extremes through targeted observations and modelling, with results communicated to partners and policy makers to support sustainable management and restoration of valuable coastal habitats. The position is part of the NERC-funded Centre for Doctoral Training, ECOWILD. The scholarship covers tuition fees for Home students and provides an annual stipend in line with UKRI recommended levels (£20,780 in 2025-26) for 44 months. The recruitment process is inclusive, considering individual circumstances to ensure fairness.

Application is via the ECOWILD website.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants should have a strong academic background in a relevant discipline such as environmental science, marine science, ecology, mathematics, computer science, or related fields. Experience or interest in field work, data analysis, coding, and climate or ecological modelling is desirable. The recruitment process is inclusive and will consider individual circumstances such as parental leave, caring duties, part-time work, or disabilities. No specific GPA or language test requirements are mentioned.

How to apply

Apply via the ECOWILD website. Visit https://ecowild.site.hw.ac.uk/how-to-apply/ for application instructions. Ensure you provide all required documents and disclose any relevant circumstances for fair consideration.

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