Health Data Analytics Graduate Fellowship: Apply Now!
The Health Data Analytics Graduate Fellowship invites postgraduate students from accredited universities to advance Health Data Analytics research in Nigeria. Eligible candidates will explore areas like AI, big data, and visual analytics. Benefits include a grant of up to ₦1M for research, job opportunities, and extensive mentorship. To apply, fill the HDA form and provide required documents, with successful applicants being notified within 8 weeks.
In the dynamic landscape of health and technology, Nigeria stands at the cusp of a transformative revolution. At the heart of this metamorphosis is the opportunity for postgraduate students to influence the future of health data analytics and, by extension, the healthcare delivery system in Nigeria. Enter the Health Data Analytics Graduate Fellowship – a pioneering initiative aimed at galvanising postgraduate talent across accredited universities.
Fellowship Name | Health Data Analytics Graduate Fellowship |
Fellowship Goal | Enhance capacity for Health Data Analytics at advanced academic & research levels. |
Objectives | Research in health analytics, support data platforms, inform HIS policy, & more. |
Eligibility | Postgrad students with valid ID from accredited universities & specific research goals. |
Research Areas | Data management, AI, health outcomes, big data, health financing, & more. |
Benefits | Up to ₦1M for research, mentorship, job opportunities, & access to datasets. |
Application Method | Complete HDA form, attach required docs, & submit 2-minute video. |
Deadline & Result | Ongoing; successful applicants notified within 8 weeks post-deadline. |
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Fellowship Aims and Objectives
The chief ambition of this fellowship rests on fortifying the capacity for Health Data Analytics and its affiliated sectors, thereby setting the tone for subsequent technological advancements in the field. The overarching objectives of this HDA fellowship encompass:
- Cultivating indigenous aptitude for research in health data analytics.
- Fortifying the evolution of robust health data platforms.
- Amplifying the efficacy and utilisation of health data and its platforms.
- Harnessing findings to mould Health Information Systems (HIS) policy frameworks.
- Facilitating the publication of research in esteemed academic journals.
Eligibility Criteria
Prospective fellows must satisfy the following prerequisites:
- Possess verifiable identification (e.g., international passport, NIN, driver’s licence).
- Be a postgraduate scholar from an accredited university.
- Undertake research focused on bolstering the Nigerian health infrastructure in areas such as:
- Data management, visual analytics, data mining, health outcomes, population demographics, health data advocacy, artificial intelligence, and many more.
Fellowship Incentives
The chosen candidates will be bestowed with:
- A research grant up to ₦1,000,000.00.
- Enrichment in health data analytics and research.
- Prospective employment openings with eHealth4everyone post-fellowship.
- Networking opportunities with like-minded individuals.
- Consistent mentorship, guidance, and provision of requisite datasets.
Application Process
To throw your hat in the ring:
- Submission: Complete the HDA fellowship form meticulously.
- Attachments: Furnish official transcripts, CVs, admission letters, statement of intent (maximum 500 words), research summaries, recommendation letters, prior publications, and a two-minute video encapsulating your research aspirations.
- Selection: The HDA fellowship committee will adjudicate applications. Successful aspirants will be intimated within 8 weeks post-deadline, requiring them to acknowledge their acceptance within a week.
Please Observe: The allotted funds are earmarked solely for research. All resultant research under the HDA fellowship will be open to use by the eHealth for Everyone Foundation and the larger community without any copyright constraints.
The opportunity is available on an ongoing basis. For a deeper understanding and more intricate details, peruse here.
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