Bacterial Learning Principles for Next-Generation Bio-Inspired AI Architectures (BAC-AI) South East Technological University (Waterford) in United Kingdom

This PhD opportunity at South East Technological University (Waterford) focuses on the project 'Bacterial Learning Principles for Next-Generation Bio-Inspired AI Architectures (BAC-AI)'. The research aims to explore how bacterial gene regulatory networks and learning mechanisms can inspire novel artificial intelligence architectures, with an emphasis on energy efficiency and sustainability. The project is interdisciplinary, combining bioinformatics, computer science, and biological systems to develop innovative computational models and AI frameworks.

The successful candidate will join the Research Support Unit and work under the supervision of Dr B Butler, Prof S Balasubramaniam, and Dr S Somathilaka. Over 48 months, the student will conduct full-time research, culminating in the award of a PhD from SETU. The project offers a unique opportunity to bridge biological principles and advanced AI, contributing to the development of next-generation bio-inspired technologies.

Applicants should have a strong academic background in computer science, bioinformatics, biology, or related disciplines. Experience with computational modeling, programming, or biological data analysis is highly desirable. The project is ideal for candidates interested in artificial intelligence, gene regulatory networks, and sustainable computing.

While funding details are not specified, candidates are encouraged to check SETU's website or contact the supervisors for potential funding opportunities. The application deadline is 22 April 2026. To apply, submit your CV, academic transcripts, and a cover letter via the provided FindAPhD link. For further information, reach out to the supervisors listed.

This position offers a stimulating research environment, access to interdisciplinary expertise, and the chance to contribute to cutting-edge developments in bio-inspired AI. Join SETU and help shape the future of sustainable artificial intelligence.