L Dorp
3 months ago
FlightPath: Predicting Avian Influenza Evolution through AI-Powered Phylodynamics and Bird Migration Modelling University of Reading in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Funded PhD Project (Students Worldwide)
Deadline
Expired
Country
United Kingdom
University
University of Reading

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About this position
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.
Funding details
Funded PhD Project (Students Worldwide)
What's required
Applicants should hold or expect to obtain a first or upper second class undergraduate degree (or equivalent) in a relevant discipline such as biology, bioinformatics, computer science, ecology, or a related field. Experience or strong interest in artificial intelligence, machine learning, and data science is highly desirable. Candidates should demonstrate strong analytical skills and a keen interest in interdisciplinary research. English language proficiency is required for non-native speakers, typically demonstrated by IELTS or equivalent.
How to apply
Interested candidates should visit the project link and follow the application instructions provided by University College London. Prepare your CV, academic transcripts, and a cover letter outlining your suitability for the project. Contact the supervisors for further information if needed.
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