International Association
for Cryptologic Research

Fully-funded competitive PhD studentship, highly suitable for UK candidates, is available.

Brief Description: Weather forecasting and environmental prediction are vital for managing risks such as flooding, extreme temperatures, and poor air quality. However, most forecasting systems rely on centralised data processing, raising concerns about privacy, data ownership, and resilience to cyber attacks or system failures. These challenges have been largely overlooked in both the UK and globally.

This project builds on recent work by Dr Aydin Abadi and colleagues at Newcastle University, who developed a decentralised weather forecasting framework combining Federated Learning (FL) and blockchain. The approach enables multiple organisations to train shared forecasting models without exchanging raw data. Blockchain ensures transparent model validation, while privacy-preserving methods protect sensitive local observations.

The PhD will extend that research by improving the scalability, accuracy, and security of decentralised environmental forecasting. It will explore advanced cryptographic techniques such as secure aggregation, privacy-preserving consensus, and private set intersection (PSI) to protect participants’ data and evaluate performance on real and synthetic meteorological datasets.

The goal is to deliver a scalable and secure collaborative forecasting framework that strengthens environmental resilience and benefits society.