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Research Associate – Epidemiology/Statistics at Kamuzu University of Health Sciences

  • Full Time
  • Blantyre
  • Salary: 00

Kamuzu University of Health Sciences

Research Associate – Epidemiology/Statistics (RE-ADVERTISED)

Kuzama pa Kalondo Project 


Malawi has made tremendous progress in combating the HIV epidemic. The country is on  track to surpass the UNAIDS 95-95-95 antiretroviral treatment (ART) and viral  suppression targets, dramatically reducing new HIV infections and AIDS-related deaths.  Now, the Malawi HIV programme’s efforts are focused on how to effectively maintain  requisite HIV services for decades to come to protect livelihoods of people living with  HIV and sustain progress.

Transitioning from rapidly scaling-up HIV programmes to monitoring sustained epidemic  control requires new approaches to monitoring the HIV epidemic and response. To date,  monitoring the HIV infection trends and associated risk factors has relied on facility- and  population-based surveillance methods, which were effective in detecting large changes  in HIV infections and programme coverage. Quantifying sustained high coverage, small  gaps, and low numbers of new infections poses new challenges.

The Kuzama pa Kalondo — ‘Getting Smart’ on HIV Surveillance Project aims to use novel  data analytic methods to track the progress Malawi is making in the fight against  HIV/AIDS. This project is being implemented by the Kamuzu University of Health  Sciences (KUHeS), Harvard T.H. Chan School of Public Health (HSPH), Nyanja Health  Research Institute, African Institute for Development Policy (AFIDEP), and University of  Cape Town (UCT), in partnership with the Directorate of HIV, STIs, and Viral Hepatitis  (DHA), the Public Health Institute of Malawi (PHIM), the US Centers for Disease Control  (CDC), and others.


An individual is required to take up a 6-month full-time position of Research Fellow based  in Blantyre or Lilongwe and participate in the following roles in the project: • Conduct literature search and review on HIV surveillance methodologies,  particularly those involving mathematical modelling;

  • Liaise with statisticians and mathematical modelers in collaborating institutions; • Participate in design and implementation of adaptive HIV household surveys, under  the supervision of project co-investigators
  • Perform data collection, extraction, cleaning and analyses;
  • Curate data extracted from anonymized Ministry of Health databases and manage  the data repositories;
  • Prepare project reports, manuscripts and policy briefs;
  • Participate in research dissemination locally and internationally
  • Supervise design of electronic data capture tools in platforms such as Open Data  Kit (ODK) app.

Contract Duration

The Research Fellow will be recruited on a fixed-term of 6 months with a view to upgrade  to a 3-year PhD fellowship.


Applicants must have a Master’s degree in Statistics or Epidemiology. Candidates with any  of the following competencies and skills will have an added advantage:

  • Bayesian statistical modelling
  • Scientific manuscripts writing and publication
  • Quantitative data analyses using multiple software packages including R and Stata  • Database development and management

Training opportunity 

The Research Fellow will undergo rigorous competence assessment within the first 6  months of recruitment. Successful candidates will be encouraged to apply and enroll in a  fully-funded KUHeS-based PhD fellowship which includes short-term training at various  international centres of excellence in mathematical modelling. Unsuccessful candidates  will not have a contract extension.

Method Of Application

Applicants must include;

  1. A motivation letter (2 page maximum),
  2. A detailed CV
  3. Certified copies of academic transcripts
  4. Authenticated copies of academic certificates (by a lawyer, magistrate, or registrar of the awarding institution)
  5. Names and emails of three referees.

Applications must be submitted via email to:

Applications should be received no later than 14th May 2024 

Those who applied should not apply again.

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