Health Data Analytics (HDA) Fellowship

This is to inform the general public that applications for the Health Data Analytics (HDA) Fellowship 2022 are now open for Nigerian Researchers and suitably qualified candidates. The goal of the HDA Fellowship aims at improving health data analytics in Nigeria with the help of advanced level research. The main objectives of this fellowship are to:

  • Build capacity for research in health data analytics
  • Support the development of health data platforms in Nigeria
  • Improve the utilization of health data and data platforms in Nigeria
  • Use findings to inform Health Information Systems (HIS) policy development in Nigeria
  • Facilitate the publication of research reports in recognized journals

 

More Information about the Health Data Analytics (HDA) Fellowship

Research goals should be targeted towards improving the Nigerian health system around the following areas:

  • Health Governance
  • Health outcomes
  • Health financing
  • Health Workforce
  • Population and demographics
  • Health facility service availability and readiness
  • Drugs and logistics
  • Service delivery
  • Health Impact
  • Health surveillance
  • Health analytics software development

The goals should be approached using any of the following methods:

  • Data Management
  • Visual Analytics
  • Data Mining
  • Data Integration
  • Multi-source data collation
  • Advanced analytics
  • Open data advocacy
  • Big Data for health
  • Data demand and use
  • Statistical modelling of health data
  • Health Information System interoperability
  • Geographic Information System (GIS)
  • Artificial Intelligence
  • Machine learning
  • Software development

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Name of Award provider: The eHealth for Everyone Foundation. Abuja, Nigeria.

Offered annually: Yes (Until January 2023)

Eligible Countries: All English speaking countries

To be taken at (country): Can be taken at eligible countries

Field/level of study: Postgraduate students in the following disciplines can apply: Public Health, Statistics and Computer Science or other related disciplines.

Selection/eligibility criteria: To be eligible for the Health Data Analytics (HDA) Fellowship, the individual must fulfill the following requirements;

Number of awardees: Not specified

Duration of scholarship: The fellowship would support research in line with the applicants academic timeline for the fulfillment of the degree.

 

Value of HDA Fellowship

The benefits of this fellowship include:

  • Up to ₦1,000,000.00 (per fellow) for postgraduate research (including research expenses e.g. equipment, data collection etc)
  • Capacity building in research and health data analytics
  • Possible job opportunities with eHealth4everyone on completion of the fellowship
  • Access to a network of individuals with shared interests
  • Mentorship and support from the administering body. This would translate into the provision of reviews and guidance during the course of their research.
  • Provision of datasets on request.
  • Must hold an acceptable form of Identification (Drivers license, National ID etc)
  • Must be a postgraduate student of any accredited University with a valid means of identification
  • Candidates should hold a Bachelor’s degree of at least a  Second class upper honors for Master’s students, and at least a distinction, Merit or its equivalent in Master’s, for PhD students.

 

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How to apply for Health Data Analytics (HDA) Fellowship

Visit Health Data Analytics (HDA) Fellowship Webpage for Details: here

Other important information: Funds are to be used for the research work ONLY. Funds would possibly cover textbooks, equipment, publications, and travels (for data collection activities etc). Costs that are indirectly related to the research would need to be approved by the HDA fellowship committee.

In addition, results from all HDA funded research will be completely open for use by the eHealth for Everyone Foundation and others. There will be no copyrighting of research.

Application deadline: Quarterly rolling basis (Until January 2023)

 

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