Strengthening Modelling and Analytics Capacity and Ecosystem for Women’s Health Project is a 3-year project funded by Bill and Melinda Gates Foundation.
The Major Objectives are to;
- Support innovative approaches to modeling of women’s health issues or broader health topics that incorporate a gender lens;
- Increase the number of trained modelers, especially women, with gender expertise based in African countries;
- Enhance strategic planning, policy engagement, and translation of research that accounts for gendered effects and insights from the context in which data are collected;
- Facilitate South-South data-centered collaborations and strengthen existing networks as well as modeling and analytics ecosystems.
The project will train modellers for a duration of 6 months (2 months didactic, and 4 months fieldwork). The 2 months training will be conducted at the National Institute of Public Health and field placement will be at various programs in the Ministry of Health with travel to other relevant data collection sites.
The project is soliciting applications for training opportunities on women’s health. Some of the areas that will be covered include: Communicable diseases (i.e. Malaria, TB, HIV), Non-communicable diseases (i.e. breast and cervical cancers), Maternal and Perinatal Mortality, Gender Based Violence, Family Planning, Health Insurance Coverage etc.
Number of opportunities on offer
The program will offer training opportunity to 8 trainees.
Expected outcome
- Acquired knowledge and skills in modelling
- Able to design a modeling project
- A completed modeling project
A draft manuscript for publication
Eligibility Criteria
- Bachelor’s degree in Statistics, Computer Science, Mathematics, Physics, Medicine and Biomedicals (Biomedical Laboratory Technology, Cytotechnology, Biomedical Engineering, Biomedical Sciences), and any other relevant fields
- Master degree will be an added advantage
- Should be nationals of Uganda
- Should be working in a health or gender related public institution
- Should be aged between 25-35 years
- Should have access to a computer
- Should have time to undertake the course