The Research Fellow provides extensive collaboration opportunities with a broad network of healthcare professionals and researchers both locally and internationally. Additionally, there is an opportunity to engage in a diverse range of innovative maternal-child health research projects. These include studies in reproductive epidemiology, nutritional epidemiology, genetic epidemiology, longitudinal health data modelling across preconception, pregnancy, and postnatal periods, as well as digital health application projects. The duties included:

• Collaborate closely with the Principal Investigator to design, plan, and execute qualitative research projects focusing on reproductive health studies.
• Independently design and conduct qualitative data collection methods such as in-depth interviews, focus groups, and observational studies.
• Analyse qualitative data using appropriate software and methodologies, providing expert guidance on thematic analysis, content analysis, and other relevant approaches in reproductive health research.
• Supervise the day-to-day progress of research projects, ensuring adherence to timelines and deadlines.
• Manage administrative responsibilities related to IRB applications, ensuring compliance with ethical, regulatory, and legal standards.
• Present research findings at national and international conferences and publish results in peer-reviewed scientific journals.
• Contribute to the development of grant proposals and reports for funding agencies.
• Collaborate with multidisciplinary teams, including healthcare providers, researchers, and public health experts from universities, government agencies, and industrial partners.
• Stay abreast of current trends and methodologies in qualitative research, particularly as they apply to reproductive health.
• Perform any other related duties as assigned by the Principal Investigator.

Job Requirement:

• PhD in Epidemiology, Biostatistics, Bioinformatics, Nutrition, Public Health Sciences, or a related discipline.
• Experience in statistical analysis using programs such as R or Stata and NVivo with a focus on health data modelling, qualitative analysis, and systematic review.
• Relevant experience in a clinical research setting.
• Exceptional written and verbal communication skills, capable of presenting complex concepts to diverse audiences.
• A track record of peer-reviewed publications.
• Experience with digital health application, AI and machine learning methods is preferred.
• Ability to work both independently and as part of a team, collaborating effectively with both immediate and extended colleagues.