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Professor

Rowland Kao

Professor at School of Informatics

University of Edinburgh

United Kingdom

Research Interests

Epidemiology

50%

Virology

30%

Disease Transmission

60%

Disease Biology

40%

Molecular Epidemiology

40%

Livestock Management

30%

Multispecies Studies

30%

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Recent Grants

Grant: Close

Molecular epidemiology of ticks and tick-borne disease, host resistance and development of novel pathogen vaccines

Open Date: 2014-09-30

Close Date: 2017-09-29

Grant: Close

Social, Economic and Environmental Drivers of Zoonoses in Tanzania (SEEDZ)

Open Date: 2014-09-30

Close Date: 2018-09-29

Grant: Close

US-UK Collab: Mycobacterial Transmission Dynamics in Agricultural Systems: Integrating Phylogenetics, Epidemiology, Ecology, and Economics

Open Date: 2014-08-31

Close Date: 2018-08-30

Grant: Close

US-UK Collab: Mycobacterial Transmission Dynamics in Agricultural Systems: Integrating Phylogenetics, Epidemiology, Ecology, and Economics

Open Date: 2014-08-31

Close Date: 2018-08-30

Grant: Close

Joint estimation of epidemiological and genetic processes for Mycobacterium bovis transmission dynamics in cattle and badgers

Open Date: 2014-06-30

Close Date: 2017-06-29

Positions(1)

Publisher
source

Oisin Mac Aodha

University of Edinburgh

.

United Kingdom

PhD in AI-Based Identification of Emerging Zoonotic Disease Hotspots

This fully funded PhD project at the University of Edinburgh's School of Informatics focuses on developing advanced AI-based solutions to identify and mitigate the spread of emerging zoonotic and infectious diseases. The research is motivated by the urgent need to address threats to human health posed by diseases such as Highly Pathogenic Avian Influenza, which are increasingly prevalent due to climate change, habitat loss, and intensified human-animal interactions. The project aims to create new computational tools for predicting disease hotspots by integrating diverse data sources, including human population data, remote sensing, and species observation records. By leveraging recent advances in multi-modal artificial intelligence and spatial modelling, the student will develop techniques to estimate global biodiversity at scales relevant to pathogen circulation and landscape management. The research will also involve identifying likely zoonotic disease hotspots using existing infection datasets and recommending land management strategies to enhance resilience against disease spread. Supervision will be provided by Dr Oisin Mac Aodha and Professor Rowland Kao, with additional mentorship and real-world data access from the Animal and Plant Health Agency (APHA), a key UK government partner. The student will be integrated into the supervisors' research groups and the broader Edinburgh Infectious Diseases network, benefiting from regular group meetings, collaborative opportunities, and tailored training to address any knowledge gaps. The project outputs will include open-access models and data products for spatial risk prioritisation and species distribution, supporting practitioners and researchers in public health and ecological fields. The work aligns with the UK Biological Security Strategy and will contribute to pandemic preparedness and biosecurity efforts. The studentship is part of the UKRI AI Centre for Doctoral Training in Biomedical Innovation and offers a comprehensive funding package: full tuition fees, a stipend of £20,780 (2025/26), and an individual budget for travel and research costs. Additional allowances for sick pay and maternity leave are included, and eligibility is open regardless of nationality or domicile. Applicants should have a strong academic background in a relevant discipline (such as computer science, biology, or mathematics), experience or interest in AI and machine learning, and good programming skills. English language proficiency must meet university standards. The application deadline is January 20, 2026. For more information and to apply, visit the project page or the University of Edinburgh's application portal. Early contact with the supervisors is encouraged for specific queries.

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Collaborators(11)

Matthew Michalska-Smith

University of Minnesota

UNITED STATES
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Kimberly VanderWaal

University of Minnesota

UNITED STATES
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Alun Lloyd

Drexel Professor of Mathematics

North Carolina State University

UNITED STATES
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Joseph Crispell

University of Glasgow

UNITED KINGDOM
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Maxim Cheeran

University of Minnesota

UNITED STATES
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Declan Schroeder

Associate Professor

University of Minnesota

UNITED STATES
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Miguel Lurgi

Associate Professor

Swansea University

UNITED KINGDOM
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Andrea Wilson

Professor of Infectious Disease Genetics and Modelling

University of Edinburgh

UNITED KINGDOM
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Meggan E. Craft

University of Minnesota

UNITED STATES
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Mikhail Churakov

Swedish University of Agricultural Sciences

SWEDEN
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Dennis Makau

University of Minnesota

UNITED STATES
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