This PhD opportunity, hosted at University College London, focuses on the prediction of Avian Influenza A virus (AIV) evolution using cutting-edge AI-powered phylodynamics and bird migration modelling. Avian Influenza viruses pose a significant threat to global health, with birds acting as the primary reservoir hosts. The project aims to integrate biodiversity, bioinformatics, ecology, evolution, zoology, artificial intelligence, data science, and machine learning to develop innovative approaches for understanding and forecasting the spread and evolution of AIVs. Students will join the AI-INTERVENE department and work under the supervision of Dr L Dorp, Dr M Escalera-Zamudio, and Prof F Balloux, who are experts in evolutionary biology, bioinformatics, and computational modelling. The research will involve the use of advanced computational techniques, including machine learning and AI, to analyze large-scale datasets on bird migration patterns and viral genetic sequences. The interdisciplinary nature of the project provides a unique opportunity to contribute to both fundamental science and practical applications in disease surveillance and control. Applicants should have a strong background in biology, bioinformatics, computer science, ecology, or related fields, and demonstrate a keen interest in interdisciplinary research. Experience with AI, machine learning, and data science is highly desirable. The project is ideal for candidates who are passionate about applying computational methods to real-world problems in global health and biodiversity. Funding details are not specified in the current announcement. The application deadline is 19 January 2026. Prospective students are encouraged to review the project details and prepare their application materials, including CV, transcripts, and a cover letter. For further information, candidates may contact the supervisors or visit the provided project link.

This PhD project, hosted at University College London (UCL) and affiliated with the University of Reading's AI-INTERVENE department, focuses on the characterisation of the biodiversity and ecology of bacteriophages through large-scale analyses of metagenomic data. Bacteriophages, viruses that infect bacteria, are the most abundant replicating entities on earth and play a crucial role in microbial ecology and evolution. The project aims to leverage advanced bioinformatics, artificial intelligence, and machine learning techniques to analyse vast metagenomic datasets, uncovering patterns in phage diversity, ecological interactions, and evolutionary dynamics. Research areas include biodiversity, bioinformatics, ecology, evolution, artificial intelligence, data science, machine learning, and statistics. The successful candidate will work under the supervision of Prof F Balloux, Dr L Dorp, and Dr C Barnes, gaining expertise in computational biology and ecological data analysis. The project offers a unique opportunity to contribute to our understanding of microbial ecosystems and the role of bacteriophages in shaping bacterial communities. Applicants should have a strong academic background in biology, bioinformatics, computer science, or a related discipline, with experience or interest in data analysis, statistics, and computational approaches. The position is ideal for candidates passionate about biodiversity, ecology, and the application of AI in biological research. English language proficiency may be required for non-native speakers. While funding details are not specified, candidates are encouraged to check the project link for updates or contact the supervisors for further information. The application deadline is 19 January 2026. To apply, review the project details, prepare your CV, academic transcripts, and a cover letter, and submit your application via the provided FindAPhD link.