Post-Graduate Fellowship-Institute for Health Metrics and Evaluation
Post-Graduate Fellowship
Location: University of Washington, USA
Last Date: November 1, 2010
Post-Graduate Fellowship
Institute for Health Metrics and Evaluation
Call for Applications
The Post-Graduate Fellowship is an intensive training program that provides opportunities both for self-directed research and interdisciplinary collaboration in health metrics. Strong candidates for this program have graduate-level training in quantitative methodology from one of the following areas: health policy, economics, mathematics, computer science, statistics, biostatistics, epidemiology, health services, demography, engineering, physics, medical sciences, or other related fields.
The Post-Graduate Fellowship (PGF) combines academic research, education and training, and professional work with progressive, on-the-job training and mentoring from an illustrious group of professors and researchers.
The purpose of the fellowship is to:
• Enhance skills in conducting in-depth, methodological research on a variety of global health topics with mentoring from faculty and researchers who are the leading minds in their fields.
• Advance knowledge of quantitative analytical methodologies and their application to global health.
• Develop understanding of the current global health landscape and its challenges.
• Strengthen the ability to design and implement research projects and mentor junior researchers.
• Prepare fellows for future positions in academia, national health agencies, international organizations, and foundations.
The Institute for Health Metrics and Evaluation is a new organization at the University of Washington. Its mission is to monitor global health conditions and health systems as well as to evaluate interventions, initiatives, and reforms. It uses cutting-edge techniques to tackle some of the most difficult and critical questions in global health and find answers that will become the foundation for better policies and, ultimately, better health.
IHME fellows work in one or two of six IHME focus areas:
• Generating systematic estimates of health outcomes, including mortality, causes of death, and the overall burden of disease.
• Measuring the coverage of specific health interventions and estimating the quality of care.
• Tracking, measuring, and analyzing donated funding for health and how it affects national government health spending.
• Estimating the costs and effectiveness of health service delivery platforms and interventions.
• Conducting impact evaluations of policies, interventions, and programs and assessing health system performance.
• Developing survey instruments and creating analytical tools to harness the value of data from national and international health information systems and from locally available sources.
Fellows receive training through on-the-job research, methods workshops, access to University of Washington courses, and on-site lectures and seminars. Fellows contribute directly to IHME’s research agenda through their involvement in work groups, development of new methods, and managing and driving research projects to meet deliverables.
Post-Graduate Fellows are appointed at IHME for one year beginning in September, with the possibility of renewal for a second year upon mutual agreement. The salary is 50,000 USD. As University of Washington employees, fellows are eligible for an insurance benefits package that includes a choice among several medical and dental insurance plans, life insurance, and long-term disability. Please note that there is no retirement package included with this appointment.
Eligibility
To be considered for a Post-Graduate Fellowship, candidates must have the following:
• A PhD or MD
• A strong quantitative background
• Advanced research experience, especially with data analysis and statistical methods.
Application requirements
Applications for the IHME Post-Graduate Fellowship are due November 1 and must include:
1. A cover letter that includes:
• Your full contact information (address, phone number, and email).
• The name, affiliation, and full contact information of three references.
• Which IHME’s areas of work you are most interested in.
• How you learned about the program.
2. Your curriculum vitae or resume.
3. A personal statement describing your interest in IHME and your professional and academic interests and objectives. Personal statements should be between 750 and 1,000 words.
4. Three sealed letters of recommendation.
5. The educational transcript from your highest degree attained. If your transcripts are not in English, please also provide a listing of all coursework with grade and credit hour information.
6. An English reprint of your most significant publication or research paper.
7. Proof of proficiency in English for candidates whose native language is not English. Candidates who have completed a degree wholly in English can provide a copy of their degree. All other candidates should send a copy of their scores on an approved English language test, specifically:
* The Princeton Test of English as a Foreign Language (TOEFL): For the paper-based test, minimum overall score of 600, including a minimum score of 5.0 in the test of written English; for the computer-based test, minimum overall score of 250, including a minimum score of 5.0 in the test of written English; for the Internet-based test, a minimum overall score of 100, including a minimum score of 24 in the test of written English.
* The British Council International English Language Testing System (IELTS): A minimum score of 7.0 overall, including a minimum score of 7.0 in the written component.
How to submit your application
Applications can be mailed to:
Institute for Health Metrics and Evaluation
University of Washington
Attention: PGF Program
2301 Fifth Ave., Suite 600
Seattle, WA 98121, USA
CVs/resumes and personal statements may be emailed to pgf@healthmetricsandevaluation.org
More information about the PGF program and the Institute for Health Metrics and Evaluation can be found at: http://www.healthmetricsandevaluation.org
Institute for Health Metrics and Evaluation
