Research Internship Clusters

The Chronic Disease Epidemiology Research Lab is dedicated to advancing evidence-based understanding of the burden, distribution, determinants, and prevention of non-communicable diseases (NCDs) across diverse populations, with particular relevance to low- and middle-income country settings. The group focuses on generating high-quality epidemiological evidence that informs public health policy, clinical practice, and disease prevention strategies.

Interns in this lab are trained to think critically about population health data, risk factors, and health inequalities, while developing strong skills in systematic reviews, meta-analyses, and scholarly manuscript development under structured mentorship.

This lab adopts a multidisciplinary and systems-oriented approach to environmental health and climate change research. It emphasises the application of robust evidence synthesis methods to evaluate the health impacts of environmental exposures and climate-related hazards, as well as the effectiveness of mitigation and adaptation strategies.

Interns in this lab receive structured training and mentorship in research design, evidence synthesis, and manuscript development, enabling them to contribute meaningfully to research that supports environmental health policy, climate resilience, and sustainable development goals.

This lab adopts a multidisciplinary global health perspective, integrating epidemiology, public health, health systems research, and policy analysis. It emphasises the synthesis of existing evidence to answer complex global health questions related to disease burden, transmission dynamics, intervention effectiveness, and health inequities. 

Research within this cluster addresses both longstanding and emerging infectious disease threats, including pandemics, endemic infections, and neglected tropical diseases. Interns are trained to critically examine global health evidence, apply rigorous systematic review methodologies, and contribute to scholarly outputs that support effective public health decision-making.

The Machine Learning & Computational Research Cluster is designed to advance research at the intersection of data science, artificial intelligence, computational modelling, and health and biomedical research. This lab focuses on applying modern computational methods to solve complex research problems, generate predictive insights, and enhance evidence synthesis and decision-making in health and related disciplines.

This lab supports research that leverages machine learning algorithms, statistical computing, and data-driven approaches to analyse large and complex datasets. Emphasis is placed on methodological transparency, reproducibility, and responsible use of AI, ensuring that computational research outputs are scientifically robust, ethically sound, and suitable for academic publication.

Interns in this lab are trained to move beyond theoretical understanding into practical application of machine learning and computational tools, while developing the ability to clearly communicate technical findings through well-structured academic manuscripts.

The Pharmaceutical & Biomedical Research Lab is dedicated to advancing high-quality research at the intersection of pharmaceutical sciences, biomedical research, and clinical evidence generation. The lab focuses on strengthening evidence around medicines, therapeutic interventions, diagnostics, and biomedical technologies, with the goal of informing clinical practice, regulatory decision-making, and health policy.

This lab places strong emphasis on evidence synthesis, translational research, and methodological rigor, supporting projects that evaluate the safety, effectiveness, and real-world impact of pharmaceutical and biomedical interventions. Research activities are grounded in internationally recognised standards for systematic reviews, meta-analyses, and biomedical reporting, ensuring outputs are suitable for high-impact academic and clinical journals.

Interns in this lab are trained to critically engage with biomedical literature, understand pharmacological and clinical research designs, and translate complex scientific findings into clear, structured, and publication-ready manuscripts under expert mentorship.

The Traditional Medicine & Consumer Health Research lab focuses on the evidence-based evaluation of traditional medical practices, herbal medicines, dietary supplements, and consumer health products within modern healthcare systems. The cluster aims to bridge the gap between traditional health knowledge and contemporary scientific standards by applying rigorous research methodologies to assess effectiveness, safety, quality, and public health relevance.

This lab is particularly committed to strengthening research capacity in settings where traditional medicine and consumer health products play a significant role in everyday healthcare decision-making. Interns are trained to critically appraise existing evidence, identify research gaps, and contribute to high-quality scholarly outputs that inform policy, clinical practice, and consumer protection.