AI for Nature: Using Computer Science to Reconnect Fragmented Freshwater Ecosystems

Laplace Expert Ltd; Southampton; Remote; GBP 18,000 - 21,000; Part time

Job summary

The University of Southampton invites applications for a PhD project that applies computer science to identify and prioritise interventions for dams and other barriers fragmenting freshwater ecosystems.

The project develops catchment-scale computational approaches to assess ecological impacts, prioritise barrier removal, and balance social and economic utility. It is highly interdisciplinary, linking AI, GIS, remote sensing and engineering within the Faculty of Engineering and Physical Sciences.

Qualifications

• UK 2:1 honours degree or international equivalent in mathematics, computer science or a related area.
• A relevant MSc and a full clean driving licence are desirable.

Education

UK 2:1 honours degree or international equivalent in mathematics, computer science or related area

MSc degree desirable

Tools

Artificial intelligence

GIS

Remote sensing

Data analysis

Catchment-scale modelling

Job description

AI for Nature: Using Computer Science to Reconnect Fragmented Freshwater Ecosystems

University of Southampton · Faculty of Engineering and Physical Sciences

England, United Kingdom

30 November 2026; exact cutoff time was not stated on the FindAPhD project page.

About This Opportunity

University of Southampton is offering a PhD that applies computer science to identify and prioritise interventions for dams, weirs and other barriers fragmenting freshwater ecosystems.

The project develops catchment-scale computational approaches to identify river barriers, assess ecological impacts and prioritise cost-effective removal or mitigation while maintaining social and economic utility. It is highly interdisciplinary, linking computer science with river ecology, GIS, remote sensing and engineering.

Level PhD

Field AI for Freshwater Ecosystem Restoration

Specialization Artificial Intelligence & Data Science

Organization Type University

Funding & Compensation

Amount Fully Funded

Funding Type Stipend

Funding Status Fully Funded

Tuition Coverage Fully Covered

Stipend Yes

Requirements

Education

Applicants must have a UK 2:1 honours degree or international equivalent in mathematics, computer science or a related area. A relevant MSc and a full clean driving licence are desirable.

Experience

Technical Skills

• Artificial intelligence
• GIS
• Remote sensing
• Data analysis
• Catchment-scale modelling

General Skills

• Interdisciplinary collaboration
• Environmental problem solving