University College London
1 week ago
PhD in Climate Change, Sewage Pollution, and Deep Learning at University College London University College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Part of the UNRISK CDT offering 15-18 fully funded NERC studentships. Funding covers full university tuition fees, a personal stipend at standard UKRI rates, £6000 individual research and training costs, £5000 per student of cohort-level training, and a Flexible Fund for special projects. International applicants must cover visa costs and the international health surcharge (IHS).
Country
United Kingdom
University
University College London

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested positions
About this position
PhD opportunity at University College London in the Department of Earth Sciences on climate change, sewage pollution, hydrology, and deep learning.
This funded project asks how a warmer, more erratic climate may affect combined sewer overflows (CSOs) in the UK. The research will build a national deep-learning pipeline to assemble a large sewer-shed dataset, link monitored CSOs with environmental and infrastructure attributes, and train models to predict spill frequency, duration, and drivers under current and future rainfall scenarios.
You will work with methods including LSTMs, explainable AI, hydrological time-series modelling, and environmental data science. The project also involves scientific software development in Python and HPC/cloud environments. The outputs are intended to support regulation, adaptation policy, and real-world water-industry impact.
Funding: fully funded UNRISK CDT studentship with full tuition, UKRI-rate stipend, research and training costs, cohort training support, and a flexible fund. UK and international applicants may apply, though international awards are limited by UKRI rules and visa/IHS costs are not covered.
Eligibility: suitable for quantitatively trained STEM applicants with strong computational and machine-learning skills; civil or hydraulic engineering background is especially relevant, but not required.
Location: London, United Kingdom.
More information: see the project page and the UNRISK website for application details.
Funding details
Part of the UNRISK CDT offering 15-18 fully funded NERC studentships. Funding covers full university tuition fees, a personal stipend at standard UKRI rates, £6000 individual research and training costs, £5000 per student of cohort-level training, and a Flexible Fund for special projects. International applicants must cover visa costs and the international health surcharge (IHS).
What's required
Applicants should be quantitatively trained STEM students with strong interest in machine learning and computational skills. The project is especially accessible to students with training in civil engineering or hydraulic engineering, though domain training will be provided by the supervisory team.
How to apply
Apply through the UNRISK website and follow the PhD project application process there. Check the project page and the UNRISK site for full instructions and eligibility details.
More information can be found here
Ask ApplyKite AI

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.