PhD Studentship: Biodiversity Digital Twin with AI & eDNA

University of Birmingham; Birmingham; On-site; GBP 18,000 - 24,000; Full time

Benefits offered by this job

Annual stipend and tuition fees (home)

Research Training Support Grant

Funding covers stipend, tuition fees,/

Job summary

The University of Birmingham invites applications for a doctoral research project on predicting biodiversity loss in freshwater ecosystems across England. The goal is to create a digital twin by integrating sediment core environmental DNA with environmental data to model dynamics under climate and pollution scenarios.

You will apply graph neural networks, including temporal and spatiotemporal variants, and develop an intuitive dashboard to help end-users assess the impact of land use and

Qualifications

• PhD studentship funded by CENTA3 DLA/NERC with stipend and fees.
• Requires at least a 2:1 UK BSc or equivalent MSc.
• International applicants may be eligible for up to 30% of cohort.

Responsibilities

• Develop state-of-the-art AI to monitor biodiversity loss under climate and pollution scenarios.
• Apply GNNs to model biodiversity data from English freshwater lakes.
• Create a digital twin by integrating eDNA and environmental data.
• Develop an end-user dashboard for assessing production processes and land use impacts.

Skills

Graph neural networks

Temporal graph networks

Spatiotemporal GNNs

Education

UK BSc 2:1

UK MSc

Tools

Python

PyTorch

Environmental DNA analysis

Job description

The University of Birmingham invites applications for a doctoral research project on predicting biodiversity loss in freshwater ecosystems across England. The goal is to create a digital twin by integrating sediment core environmental DNA with environmental data to model dynamics under climate and pollution scenarios.

You will apply graph neural networks, including temporal and spatiotemporal variants, and develop an intuitive dashboard to help end-users assess the impact of land use and