Epidemiologist (18-month Contract)

About the role

We are seeking a Postdoctoral Researcher in Arbovirus Epidemiology and Data Science to join the Epidemiology Department at the Mahidol Oxford Tropical Medicine Research Unit (MORU) in Bangkok and work on the PANDAI (Pandemics AI Observatory) project.

PANDAI is an international research programme developing epidemiology-informed AI to strengthen infectious disease surveillance, outbreak detection, risk assessment, forecasting and public-health decision support. The successful candidate will play a central role in PANDAI's arbovirus use case, focusing particularly on dengue and West Nile virus. They will lead the collation, harmonisation and epidemiological analysis of arbovirus data and the development of approaches for risk assessment and public-health response, while working closely with the project's AI team at Oxford. Based within MORU's Epidemiology Department in Bangkok, the postholder will work alongside epidemiologists, data scientists, geospatial researchers and public-health specialists and collaborate with WHO, national public-health authorities and PANDAI partners across Asia and Europe.

Key responsibilities

• Identifying, collating, harmonising and documenting arbovirus surveillance and relevant contextual datasets from multiple countries and sources
• Conducting epidemiological, spatial and temporal analyses of dengue, West Nile virus and other arbovirus data
• Developing and evaluating approaches for geographically specific infectious-disease risk assessment, incorporating information on transmission, populations, vectors, environment, health-system capacity, preparedness and other relevant factors
• Developing evidence-based approaches to translate risk assessments and forecasts into appropriate public-health response and preparedness options
• Working closely with PANDAI's Oxford AI team to provide the epidemiological knowledge, curated datasets, analytical outputs and domain expertise needed for development and validation of PANDAI's AI models
• Contributing to the evaluation of model performance, uncertainty, generalisability and usefulness for real-world public-health decision-making
• Working with WHO, Ministries of Health and other partners to ensure that PANDAI's risk-assessment and decision-support approaches address operational public-health needs
• Developing and leading independent analytical research within PANDAI, taking advantage of the project's multinational datasets, methods and collaborations
• Leading and contributing to peer-reviewed publications, conference presentations and other scientific outputs

About you

• Postgraduate qualification (Master's or doctoral degree preferred) in epidemiology, public health, biostatistics, infectious diseases, population health, or a closely related quantitative discipline; or equivalent relevant experience
• Background in infectious-disease epidemiology, biostatistics, data science, mathematical modelling, geospatial epidemiology or a related discipline
• Experience analysing complex epidemiological or surveillance datasets
• Strong programming skills in R and/or Python
• Experience collaborating with data-science, machine-learning or AI teams, particularly in health applications
• Strong understanding of epidemiological study design, surveillance concepts, bias, confounding, causal interpretation and quantitative methods
• Experience working with complex datasets, including data cleaning, quality assessment, documentation and interpretation
• Ability to communicate epidemiological concepts clearly to multidisciplinary collaborators, including data scientists and non-specialist stakeholders
• Strong scientific writing skills and experience contributing to reports, protocols, manuscripts or other research outputs
• Fluent written and spoken English

About us

PANDAI is a Horizon Europe-funded international consortium developing a Pandemics AI Observatory to strengthen pandemic preparedness, detection, prediction, monitoring and response. The project brings epidemiological expertise together with advanced AI, global data and public-health decision-making, working with the World Health Organization and other consortium partners.

Candidate profile

We are looking for a quantitatively strong researcher with a background in infectious-disease epidemiology, biostatistics, data science, mathematical modelling, geospatial epidemiology or a related discipline.

Candidates should have experience analysing complex epidemiological or surveillance datasets and strong programming skills in R and/or Python. Experience with arboviruses or other vector-borne diseases would be advantageous, as would expertise in spatial or spatiotemporal analysis, risk modelling, infectious-disease forecasting, Bayesian methods, climate and environmental data, mobility data or public-health surveillance.

Direct expertise in artificial intelligence is not required. The postholder will work alongside specialist AI researchers and will bring complementary expertise in epidemiology, data analysis, risk assessment and public-health application.

Research opportunities

A major component of the position will be the opportunity to develop an independent programme of analytical research within PANDAI. The project will bring together large and diverse datasets across multiple diseases, countries and transmission settings, creating opportunities to develop new research questions in arbovirus epidemiology, spatial risk, surveillance, forecasting and public-health response.

The post would therefore suit an ambitious early or mid-career researcher who wants both to contribute to a major international collaborative project and to lead their own analyses, publications and methodological research.

The successful applicant should have good communication skills. Interested applicants, please submit your application with detailed resumé to the Head of Epidemiology

Professor Richard Maude

Mahidol-Oxford Tropical Medicine Research Unit (MORU)
Faculty of Tropical Medicine, Mahidol University
420/6 Rajvithi Road, Bangkok 10400

MORU’s Commitment to Equity, Diversity, and Inclusion
MORU is committed to creating an inclusive culture and a respectful environment, and values diversity and promoting equity for all its members. MORU does not tolerate any form of harassment or victimisation and expects all members, visitors and contractors to treat each other with respect, courtesy and consideration. Successful candidates are expected to adhere to these standards and principles.