Ethiopian Public Health Institute Child Health Fellow Jobs in Ethiopia

Ethiopian Public Health Institute Child Health Fellow Jobs in Ethiopia


  • The fellow will be hosted by the National Data Management Center for Health (NDMC) at Ethiopian Public Health Institute (EPHI).

  • The NDMC at the EPHI is a responsible center to archive health and health-related data, process and manage health research, apply robust data analytic technics, synthesize evidence and to ensure evidence utilization for decision making by the Federal Ministry of Health (FMoH) and other relevant stakeholders at local, sub-national and national and international levels.

  • The Child Health fellow will support a range of researches that use secondary data and evidence generation activities of the center to produce policy relevant documents for the Federal Ministry of Health and other stakeholders.

  • NDMC specifically seeks to develop a deeper understanding of the risk factors contributing to poor maternal, neonatal, and child health outcomes and how best to address them through new data analysis tools and techniques.

  • This will assist the health sector to direct and intensively apply its resources towards these covariates in-order to reduce childhood mortality and to attain targets set both in Sustainable Development Goal (SDG) and in national plans, Moreover,it’s important to examine the association between selected child health and mortality indicators by inter-linking maternal, parental, background and environmental characteristics.

  • It is highly advised and important to explore the trend and determinants of Neonatal, Infant, Child, and under-five mortality in order to reduce vulnerability and maximize child’s survival.

  • Therefore, it is important to use sound statistical methods and various data sources to determine which factors are strongly associated with child mortality, which in turn will help inform the design of intervention strategies.

  • There are key knowledge gaps in our understanding of how nutrition, prenatal and antenatal care, maternal support, and environmental and social factors contribute to an elevated risk of adverse child health outcomes and the degree to which early life experience have a lifelong sequel, or even intergenerational consequences for health and productivity.

  • Understanding these factors is required to determine what interventions, including health policies, should be delivered to which specific groups of individuals and at what point in their lifecycle to ensure optimal outcomes through the most effective use of healthcare resources.

  • The purpose of this call is therefore to hire a well experienced, high caliber fellow to explore the trends and identify the factors associated with children hood mortality, identifying and quantifying determinants for childhood mortality and child health, identifying and quantifying high impact interventions for reducing childhood mortality and those improving child survival, identifying and quantifying co-variates crucial to achieving SDG and national targets, exploring equity and quality factors impacting child health and childhood mortality including coverage of interventions, projecting the coverage or progressions of the determinants to quantify the changes in childhood mortality trends.

  • The fellow should be well versed with various childhood mortality modeling works and able to provide expert opinion for NDMC data analytic and modeling team. Moreover, the fellow is expected to prepare guidelines and documentation for steps and methodologies used in the process of selecting covariates.

  • The documents must be comprehensive in providing full contents starting from data processing (pre-processing, checking collinearity), models (for ranking and selecting determinants, for predicting survival status given certain values for determinants), and analytical steps.

  • Work in
    close collaboration with teams working on Child Health and Childhood Mortality data search and review, analysis, modeling, forecasting, sub-national disease burden estimation and evidence generation and translation

  • Undertake systematic reviews, in-depth analysis, meta-analysis to provide needed data/information on determinants, high impact interventions, intervention coverage, important co-varieties for the data analytic and visualization team working on Child Health and Childhood Mortality

  • Provide epidemiological and statistical advice to the data analytic and modeling team on principles, standards and sound methods for analyzing Child Health and Childhood Mortality data.

  • Provide subject matter inputs for Child Health and Childhood Mortality modeling work of the center

  • Work with Maternal, newborn and Child Health research data systems archived within NDMC/EPHI central repository including Surveys, Longitudinal, and Surveillance as in Health and Demographic Surveillance Site (HDSS) data, District Health Information System (DHIS2), Demographic and Health Survey (DHS), Census data from CSA, research data…

  • Advise the data analytic and visualization team on data harmonization, integration and sound statistical methods/principles for Child Health and Childhood mortality analysis

  • Coordinate with FMoH, RMNCH team, Universities and International collaborators to get methodological inputs on Child Health and Childhood Mortality modeling and to generate strong policy-relevant evidence.

  • Perform advanced epidemiologic, statistics, quantitative and qualitative analyses on Child Health and Childhood Mortality

  • Assist in drafting different types of Child Health and Childhood Mortality research proposals for grant application

  • Support in planning and undertaking data integration and analysis to generate strong public health evidence

  • Advise data search and review team on mapping and archiving of Child Health and Childhood Mortality data, data integration and triangulation.

  • Contribute in the technical working groups, committees and other engagements of the center and the institute

  • Support NDMC collaboration endeavors with research data source, data analytics, evidence generation and translation and sub-national disease burden estimates

  • Identify evidence demands within EPHI, FMOH, regional health bureaus and public health institutes.

  • Develop guidelines, Standard procedures and protocols as needed to standardize routine activities and newly adopted practices on Child Health and Childhood Mortality.

  • Disseminating evidence and findings through different outlets including; publication, evidence briefs, seminar presentations

    Job Requirements

  • Master in Maternal and Child Health, Reproductive, Maternal, Newborn and Child Health

  • Background in health Sciences ,

  • At least 5 years experiences working on Child Health

    Desired Skills and Experiences

  • Strong interpersonal, writing and organizational skills.

  • Attention to detail and ability to effectively and efficiently perform multiple tasks and balance competing priorities often within a required timeframe.

  • Ability to respond and adapt quickly to changing requirements and competing demands.

  • Ability to take initiative and/or respond independently to situations.

  • Has a good balance of knowledge and understanding across the scientific and analytical aspects associated with Child Health and Childhood Mortality.

  • Be familiar with local and international research ethics

  • Good knowledge and experience on disease epidemiology and health risk factors in Ethiopia in general and on Maternal, newborn and Child Health in particular.

  • Demonstrated experience in presenting at local, national and international scientific forums

  • Having publication and being the first or last author

  • Solid team work experiences

  • Experience working with large datasets. Extensive knowledge of statistical methodologies including hypothesis testing, linear regression, modeling, simulation, and analysis of variance.

    How to Apply

    For more information and job application details, see; Ethiopian Public Health Institute Child Health Fellow Jobs in Ethiopia

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